Apparatuses, methods and systems for a digital conversation management platform

ABSTRACT

The APPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATION MANAGEMENT PLATFORM (“DCM-Platform”) transforms digital dialogue from consumers, client demands and, Internet search inputs via DCM-Platform components into tradable digital assets, and client needs based artificial intelligence campaign plan outputs. In one implementation, The DCM-Platform may capture and examine conversations between individuals and artificial intelligence conversation agents. These agents may be viewed as assets. One can measure the value and performance of these agents by assessing their performance and ability to generate revenue from prolonging conversations and/or ability to effect sales through conversations with individuals.

RELATED APPLICATIONS

This application is a continuation of and hereby claims priority under35 USC §120 to co-pending U.S. non-provisional patent application Ser.No. 13/558,914, filed on Jul. 26, 2012, entitled “Apparatuses, MethodsAnd Systems For A Digital Conversation Management Platform”, and is acontinuation of co-pending U.S. non-provisional patent application Ser.No. 13/013,158, filed on Jan. 25, 2011, entitled “Apparatuses, MethodsAnd Systems For A Digital Conversation Management Platform”, which inturn claims priority under 35 USC §119 for U.S. provisional patentapplication Ser. No. 61/298,130, filed Jan. 25, 2010, and U.S.provisional patent application Ser. No. 61/360,434, filed Jun. 30, 2010,both entitled “Apparatuses, Methods And Systems For A DigitalConversation Value Exchange Tool.”

This application is related to Patent Cooperation Treaty ApplicationSerial No. PCT/GB2011/050119, entitled “Apparatuses, Methods And SystemsFor A Digital Conversation Management Platform,” filed on Jan. 25, 2011.

The entire contents of the aforementioned applications are hereinexpressly incorporated by reference.

This patent application disclosure document (hereinafter “description”and/or “descriptions”) describes inventive aspects directed at variousnovel innovations (hereinafter “innovation,” “innovations,” and/or“innovation(s)”) and contains material that is subject to copyright,mask work, and/or other intellectual property protection. The respectiveowners of such intellectual property have no objection to the facsimilereproduction of the patent disclosure document by anyone as it appearsin published Patent Office file/records, but otherwise reserve allrights.

FIELD

The present invention is directed generally to an apparatuses, methods,and systems of virtual asset management, and more particularly, toAPPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATION VALUEEXCHANGE PLATFORM.

BACKGROUND

Traditionally, advertising and marketing industries have conductedmarketing surveys to learn about consumer preferences and behaviors.Such information may be obtained in various ways, for example, withface-to-face interviews, user filled questionnaires, and/or the like.

SUMMARY

The APPARATUSES, METHODS AND SYSTEMS FOR A DIGITAL CONVERSATIONMANAGEMENT PLATFORM (“DCM-Platform”) transforms digital dialogue fromconsumers, client demands and, Internet search inputs via DCM-Platformcomponents into tradable digital assets, and client needs basedartificial intelligence campaign plan outputs.

In one embodiment, a method is disclosed, comprising: receivinginformation indicating a demand for a digital conversation asset;determining a type of the demanded digital conversation asset;initializing an exchange procedure for the determined type of thedemanded digital conversation asset; obtaining information required bythe exchange procedure for the determined type of the demanded digitalconversation asset; and determining an index of the demanded digitalconversation asset at least based on the obtained information for thedetermined type of the demanded digital conversation asset.

In one embodiment, a method is disclosed, comprising: instantiating aconversational artificial-intelligence agent; identifying an individualtarget for conversation; initiating a conversation with the individualtarget by the artificial-intelligence agent by providing a first portionof a conversational dialogue to the individual target; recording aresponse from the individual target to the first portion of theconversational dialogue; and responding to the response from theindividual target with a next contextual portion of the conversationaldialogue.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying appendices and/or drawings illustrate variousnon-limiting, example, innovative aspects in accordance with the presentdescriptions:

FIG. 1 shows a block diagram illustrating DCM-Platform and affiliatedentities 100 within embodiments of the DCM-Platform;

FIGS. 2A-2D show data flow diagrams illustrating embodiments of theDCM-Platform;

FIG. 3 shows a logic flow diagram illustrating interactions betweenentities within embodiments of the DCM-Platform;

FIG. 4A-4D show diagrams illustrating monetizing a conversation assetwithin embodiments of the DCM-Platform;

FIG. 5A-5C show diagrams illustrating monetizing a conversation AIentity asset within embodiments of the DCM-Platform;

FIG. 6A-6C show diagrams illustrating monetizing a portfolio assetwithin embodiments of the DCM-Platform;

FIG. 7A-7D show diagrams illustrating monetizing an exchange assetwithin embodiments of the DCM-Platform;

FIGS. 8A-8B show logic flow diagrams illustrating pricing a digitalconversation asset within embodiments of the DCM-Platform;

FIG. 9 shows a logic flow diagram illustrating consumer-agentconversation capturing within embodiments of the DCM-Platform;

FIGS. 10A-10F-3 show logic flow diagrams illustrating creating adialogue agent within embodiments of the DCM-Platform;

FIGS. 11A-11L show logic flow diagrams illustrating generating aninteractive dialogue within embodiments of the DCM-Platform,

FIGS. 12A-12D show logic flow diagrams illustrating dialogue analyticswithin embodiments of the DCM-Platform;

FIGS. 13, 14A-14B show exemplar screen shots illustrating embodiments ofthe DCM-Platform;

FIGS. 15A-15F show diagrams illustrating dialogue agents marketingwithin embodiments of the DCM-Platform;

FIGS. 16A-16D show diagrams illustrating dialogue knowledge flows withinembodiments of the DCM-Platform;

FIG. 17 shows a block diagrams illustrating components withinembodiments of the DCM-Platform; and

FIG. 18 shows a block diagram illustrating embodiments of a DCM-Platformcontroller;

The leading number of each reference number within the drawingsindicates the figure in which that reference number is introduced and/ordetailed. As such, a detailed discussion of reference number 101 wouldbe found and/or introduced in FIG. 1. Reference number 201 is introducedin FIG. 2, etc.

DETAILED DESCRIPTION

This disclosure details an implementation of apparatuses, methods, andsystems for a digital conversation value exchange platform (hereinafter,“DCM-Platform”). The DCM-Platform implements an application wherebyvirtual commodities such as digital conversation assets are created,evaluated and traded. In one embodiment, the DCM-Platform may captureand examine conversations between individuals and artificialintelligence conversation agents. These agents may be viewed as assets.One can measure the value and performance of these agents by assessingtheir performance and ability to generate revenue from prolongingconversations and/or ability to effect sales through conversations withindividuals. In one implementation, the DCM-Platform may initiate anexchange procedure by collecting required information for the exchange,and determine a pricing index for the digital conversation asset to betraded.

In one embodiment, a Robot Operating System (ROS) may be employed forboth consumer robots and other intelligent devices. For example, in oneimplementation, the DCM-Platform may employ ROS as a platform to manageintelligence hardware abstraction, consumer interfacing, low-leveldevice control, implementation of controlling and recording consumerconversations, message-passing between processes, application packagemanagement, and/or the like.

In one embodiment, the DCM-Platform may specify, store and manageinteractive voice dialogue between a consumer and an artificialintelligence agent in formats such as, but not limited to, VoiceXML(VXML), and/or the like. For example, in one implementation, a VXMLdocument may take a form similar to the following:

<vxml version=“2.0” xmlns=“http://www.website.org/2001/vxml”>  <form>  <block>    <prompt>     What is your favorite ice-cream flavor?   </prompt>   </block>  </form> </vxml>

In one embodiment, the DCM-Platform may establish and manage consumerinteractions via a virtual world platform.

In one embodiment, the DCM-Platform may employ mobile operating systems(Mobile OS) to control mobile devices within embodiments of theDCM-Platform operation. For example, in one implementation, Mobile OSsuch as, but not limited to, Google Android, Windows Mobile, iPhone OS,Symbian OS, and/or the like, may be employed.

It is to be understood that, depending on the particular needs and/orcharacteristics of a DCM-Platform application, associated security datasources, associated operating system, user interface, object,administrator, server, hardware configuration, network framework, and/orthe like, various embodiments of the DCM-Platform may be implementedthat enable a great deal of flexibility and customization. The instantdisclosure discusses embodiments of the DCM-Platform primarily withinthe context of digital conversation value exchange. However, it is to beunderstood that the system described herein may be readilyconfigured/customized for a wide range of other applications orimplementations.

For example, aspects of the DCM-Platform may be adapted for generalvirtual commodity management, pricing and exchange, and/or the like.

DCM-Platform

FIG. 1 shows a block diagram illustrating DCM-Platform and affiliatedentities 100 within embodiments of the DCM-Platform. Within variousembodiments, one or more consumers 102(a)-(d), consumer device(s)101(a)-(d), artificial intelligence (AI) agent(s) 130(a)-(b),DCM-Platform 120, DCM-Platform database(s) 119, a virtual applicationexchange platform 139, a financial trading platform 140, distributedexternal DCM-Platforms 125, DCM-Platform client(s) 135 and DCM-Platformdatabase(s) 119 are shown to interact via various communicationchannels.

In one embodiment, a consumer 102(a)-(d) may operate a variety ofconsumer devices, such as, but not limited to a cellular phone 101(a), asmartphone 101(b), a computer 101(c), a telephone 101(D) and/or thelike, to have a conversation with an AI agent 130(a)-(b). For example,the consumer may talk to the AI agent over the phone, or type texts inan instant messenger, and/or an online chatting platform to communicatewith the AI agent.

In one implementation, the AI agent 130(a)-(b) may comprise anartificial intelligence ROS and/or other intelligent devices. The AIagent may communicate with, and/or be monitored by the DCM-Platform 120,which may employ the AI agent to furnish intelligence hardwareabstraction, consumer interfacing, low-level device control,implementation of controlling and recording consumer conversations,message-passing between processes, application package management,and/or the like. For example, in one implementation, the DCM-Platformmay retrieve knowledge and dialogue scripts from the DCM-Platformdatabase 119 to generate interactive dialogue steps and scripts, andsend it to the AI agent. In one implementation, the DCM-Platform may beimplemented within a central server. In alternative implementations,there may be distributed DCM-Platforms 125 to control a cluster of AIagents.

In one embodiment, the DCM-Platform may receive interactive dialoguesfrom the AI agents and encapsulate the digital dialogue scripts togenerate tradable virtual assets for exchange on a virtual applicationexchange platform 139, and/or a financial trading platform 140. In oneembodiment, the digital conversation between a consumer and an AI agentmay provide information indicating the consumer's preferences and thususeful for new advertising inventory and other forms of revenues forDCM-Platform clients 135. Within embodiments, the digital assetscomprising digital dialogue assets may be purchased by DCM-Platformclients and/or knowledge agents 135. For example, a DCM-Platform clientmay purchase the digital asset to perform data mining to obtainknowledge and information from the digital conversations. In oneimplementation, the DCM-Platform clients may comprise an AI agent, aDCM-Platform, an advertising company, and/or the like.

In another implementation, a DCM-Platform may devise marketing plansusing AI agents for the DCM-Platform clients, and the DCM-Platformclients may purchase virtual avatar AI advertising service from theDCM-Platform from the virtual application exchange platform 139. Forexample, a virtual advertising avatar may be employed to communicatewith consumers for advertising purposes via a variety of media channels,such as, but not limited to print media 135(a), television 135(b), radio135(c), Internet 135(d), and/or the like.

In a further implementation, the DCM-Platform 120 may generate tradablefinancial instruments backed by the virtual assets and facilitatetransactions of the financial instruments. In one implementation, thedigital assets may be used to generate a variety of financialinstruments, such as, but not limited to futures, forwards, options,and/or the like, to be traded on a financial trading platform 140, e.g.,the New York Stock Exchange, and/or the like. For example, investors 144of the digital assets may purchase stock shares of an AI agent (e.g., adigital asset owner, etc.) via the financial trading platform 140, asfurther illustrated in FIGS. 4A-7D and 8A-8B.

FIG. 2A shows a block diagram illustrating DCM-Platform data flowswithin embodiments of the DCM-Platform. In one embodiment, a consumer102 may exchange dialogues 205(a)-(b) with an AI agent 130(a)-(b),wherein the AI agent may comprise a computer employing an AI robotsystem. For example, in one implementation, a consumer may talk to arobot calling system over his cellular phone or telephone, and the audioconversation may be recorded and saved as a dialogue 105(a)-(b). Foranother example, a consumer may interact with a robot avatar on aninstant messenger platform (e.g., iRobot, etc.), an avatar on a socialmedia platform (e.g., Facebook, LinkedIn, Twitter, etc.), and thetextual dialogue scripts 205(a)-(b) may be exchanged and saved.

Within implementations, the AI agent may encapsulate one or more savedconversation between the consumer and the AI agent to generate a digitalasset, which is referred to as the conversation asset 210(a)-(b). Whenthe digital conversation is owned by an AI Agent, one or moreconversation asset with related topic may be encapsulated as an AIEntity asset 220(a)-(b), and the actual digital conversation componentis referred to as a Conversation Asset 210(a)-(b). For example, an AIentity may combine one or more conversations with regard to the sameadvertising project (e.g., a new product promotion, etc.) as an AIentity asset.

Within various implementations, the AI Entity assets 220(a)-(b) may besent to the DCM-Platform 120, wherein the DCM-Platform may group the AIEntity assets to form a Portfolio asset 230. In one implementation, theDCM-Platform may group AI entity assets from AI agents employed by thesame client, and/or the same advertising project as a Portfolio asset.For example, a number of AI agents, e.g., social media avatars, robotmessengers, robot callers, etc., may be employed for a new product'smarket promotion, and the digital assets from all the AI agents withregard to the product campaign may be grouped as a Portfolio asset. Infurther implementations, a collection of Portfolio assets may be tradedwithin a trading platform 140 and thus it is known as an Exchange asset240. For example, Portfolio assets 230 related to similar products maybe grouped and traded as an Exchange asset 240. Within implementations,the DCM-Platform may store the Portfolio asset 230 and the Exchangeasset 240, and/or the transaction record 245 at the database 119.Examples of types of digital assets, including the conversation assets210(2)-(b), AI entity assets 220(a)-(b), portfolio assets 230, exchangeassets 250, and/or the like, are further illustrate in FIG. 2B.

In one implementation, a DCM-Platform client 130 may purchase thedigital asset in the form of exchange asset 250 from the trading form,which may be further illustrated in FIG. 8. In an alternativeimplementation, exchange assets 250 may be traded between AI entities asdifferent asset owners, as further illustrated in FIGS. 4A-7D. Inanother implementation, investors 144 of the virtual assets may purchasestock shares 217 from the financial trading platform 140, wherein thestock shares are generated at the DCM-Platform based on the assetinformation 208 submitted by the asset owners 215.

FIG. 2B provides a block diagram illustrating DCM-Platform dataencapsulations within embodiments of the DCM-Platform. In oneembodiment, DM-Platform may create four classes of assets within digitalconversations.

In one implementation, the conversation asset 210 may be created toinclude the dialogue interactions between AI entities and humans, and/oramongst AI entities. In one implementation, an AI entity asset 220 maycomprise one ore more conversation 210 and the means, such asintelligence hardware abstraction, consumer interfaces, and/or the like,for conducting digital conversations included in the conversation asset210. In one implementation, the portfolio asset 230 may include aplurality of AI entity assets and/or the conversation assets, whereinthe portfolio asset 230 provides a branded vehicle for theaccreditation, aggregation and performance of conversation assets and AIentity assets. In a further implementation, the exchange asset 240 mayinclude one or more portfolio assets grouped together to be traded on apublic trading platform, wherein the exchange asset 240 providesaccreditation, aggregation and performance of portfolio assets 230within a public or private domain.

For example, in one implementation, an intelligent messenger avatar mayinteract with consumers on the messaging platform to provide informationwith regard to hair styling. The conversation scripts between the avatarand one or more consumers may be encapsulated as a package, which formsa conversation asset associated with the intelligent messenger avatar,and the identification information, such as the account information ofthe avatar account, together with the conversation asset may form an AIentity asset. In one implementation, similar conversations fromdifferent AI entities, such as conversations related to a new hairstyling product, may be grouped by the DCM-Platform to create aportfolio asset, wherein the portfolio asset may be labeled and/orassociated with the new hair styling product. In one implementation, thehair styling product portfolio asset may be traded with other portfolioassets (e.g., portfolio assets related to other hair treatment products)in a transaction, which may be referred to as the exchange asset in thetransaction.

Within embodiments, various data structures, objects, and relationalstructures may be adopted for creation, storage and implementations ofthe conversation asset 210, AI entity assets 220, portfolio assets 230and exchange assets 240. For example, in one implementation, an exemplarXML implementation of conversation assets 210 may take a form similar tothe following:

... </Title> Joe_Doe_Hair_dresser_0001 </Title> </Description> MessengerHair Salon customer service </Description> </Asset_Owner> Robot Corp<Asset_Owner> </Global_Identifier> RObotCorp_JoeDoe_Hair_hhhht<Global_Identifier> <Status> draft </Status> <Shares number> ...</Shares number> <platform> AOL </Platform> <OS> Windows 200X, XP </OS><Compatibility> Paml OS, BlackBerry OS </Compatibility> ...

In one embodiment, DCM-Platform may generate tradable assets based onthe digital conversations 251. Within implementations, DCM-Platform maydetermine dollar values of the digital assets 210-240, monetize theconversation 253, and determine conversation stock shares 252 andconversation index 254 for exchange, as further illustrated in FIGS.4A-8B.

In one embodiment, as digital conversations may be measurable at thelowest common denominator of a dialogue-step, a digital conversation maybe commoditized as conversation stock 252, which is a tradableinstrument. The commoditization is based on encapsulation of the digitalconversation script with a wrapper that contains all the means for theexchange of value, which is represented as conversation monetization253. Within implementations, DCM-Platform may generate a conversationindex 254 to monitor the conversation monetization together with thedigital conversation interactions from an AI end.

Within implementations, trading prices of conversation assets forexchange may be determined by market dynamics (e.g., NYSE index, etc.),which may be affected by authorship, ownership and monetization ofdigital conversation and by whether the conversation assets areaccredited as part of a branded portfolio. The value may be alsoinfluenced by the brand of the exchange chosen for the trading of value.Included are past, present and future digital conversation for valuationof conversation assets in context to individuals, both in terms of humanand artificial intelligence entities. In one embodiment, DCM-Platformmay assess conversation liquidity and generate conversation index, whichincludes the emergent patterns of conversational trends and evolution.

In one embodiment, the methods that affect the pricing of digitalconversation assets may further include, but not limited to searches andmatches of conversational needs, conversation access rights,conversation events, conversation handoffs, conversational learningloops conversational references and conversational transaction, with theassociated rules of engagements for conversation assets includingreputational, ownership transfers, withdrawals or suspension fromalgorithmic trading, and/or the like.

FIG. 2C provides a data flow diagram illustrating conversationinteractions within one embodiment of the DCM-Platform. Withinembodiments, the consumers 102 may interact with AI agents 130(a)-(b) toengage in a dialogue. The AI agent(s) 130(a)-(b) may provide dialogueactions 205(b) to a consumer 102 via a dialogue platform, and theconsumer 102 may submit s dialogue response 205(a) in return. Forexample, in one implementation, the AI agent 130(a)(b) may be an avataridentity on a social media platform, such as, but not limited to AOLmessenger, Facebook, eBlogger, LinkedIn, Twitter, and/or the like, andpost a dialogue line via the social media platform, e.g., “would youlike a 30% cash-back discount?”. The consumer 102 may then respond viathe social media platform by submitting a line “Yes. What is it?”. Inone implementation, the conversation between the consumer 102 and the AIagent 130(a)-(b) may continue in a progressive manner, as furtherillustrated in FIGS. 10A-11L.

In one implementation, the AI agents 130(a)-(b) may receive inquiriesfrom the consumer 102 during a dialogue. For example, the consumer maysubmit a dialogue line “where can I buy a hair dresser with the 30%cash-back discount?” In one implementation, the AI agents may thenconnect to an Internet search engine, such as, but not limited toGoogle, Bing, Yahoo, and/or the like, to obtain search results 247 fromthe search engines based on key words 245 search “hair dresser cashback,” and/or the like.

In one implementation, the AI agents may wrap the recorded digitaldialogue scripts with consumers to generate digital assets 255 andsubmit to the DCM-Platform for trading on an exchange platform. In oneimplementation, a client 130, such as an advertising company, etc., mayinteract with the DCM-Platform 120 to submit a marketing request 250 toemploy AI agent for advertising purposes. The DCM-Platform may thendevise marketing strategy 260 for the client and deploy the strategywith AI agents.

For example, in one implementation, a hair dresser manufacturer mayrequest the DCM-Platform devise a marketing strategy for their new hairdresser product. The DCM-Platform may analyze previously stored consumerdialogues, e.g., to extract information related to consumer preferencesof hair dressers, etc., and then devise a dialogue application andselect AI agents to implement the application, as further illustrated inFIGS. 10A-11L.

FIG. 2D provides a data flow diagram illustrating knowledge accumulationwithin one embodiment of the DCM-Platform. In one embodiment, theknowledge acquirers 261, e.g., consumers, etc., may interact with AIagents 130(a)(b) through conversation to access contextual brandedJust-in-Time high quality knowledge 265(a), which maybe free or pricedto use. For example, the AI agent(s) may provide information with regardto new products, services, and/or the like, to the knowledge acquirersduring the interactive dialogues. For another example, the knowledgeacquirers may submit responses to the knowledge received, which in turnprovide knowledge 265(b) to the AI agents, such as, but no limited toconsumers' ratings, comments of a product, and/or the like.

In one implementation, the knowledge 265(a)-(b) may be wrapped, stored,and/or filtered through dialogue scripts from a knowledge bank 265database. In one implementation, the knowledge bank database 260 may bea central database maintained by the DCM-Platform. In alternativeimplementations, the knowledge bank database 260 may comprise aplurality of mutually connected distributed databases.

In one embodiment, knowledge providers 262 may comprise the consumerbrands advertising to disseminate their “knowledge” about their productsor services. In one implementation, the knowledge providers 262 mayconvert their branded procedural knowledge 267 and incorporate them intoAI agent applications via the knowledge bank database 260. In anotherimplementation, the knowledge providers 262 may obtain consumerfeedbacks from the knowledge bank 260 and/or the AI agents viaimplementations of the AI agent applications.

In a further implementation, the market may be seeded with AI agentapplications containing high quality knowledge across a few consumerproducts brands, and the DCM-Platform may create and sell advertisingtools for User Generated Virtual Agent Apps to accelerate the populationof AI agent applications, each containing specific knowledge. Forexample, the knowledge provider 262 may purchase AI agent applicationtemplates to imbue and update their latest product information foradvertising with consumers.

Within embodiments, knowledge distributers 263 may comprise Internetsearch engines, social media platforms, such as, but not limited toApple, Google, Microsoft, RIM, and/or the like, which have channels tomarket and would benefit from new revenue streams driven by AI agents.In one implementation, the knowledge distributors 263 may obtainknowledge (e.g., brand/product information) from the knowledgeproviders. For example, the knowledge provider may post advertisementscontaining product information 267 on the World Wide Web (www) indexedby the search engines. In another implementation, AI agents may accessthe knowledge distributors 263 to search and learn knowledge 266. Forexample, the AI agents may conduct a key-word search on a search engineplatform to obtain knowledge for an on-going conversation with aconsumer.

In a further implementation, DCM-Platform may create AI agentapplication for exchange, e.g., an AI application sold in the AppleiTunes Store, etc. In one implementation, the AI agent applications maybe connected to the knowledge bank database 260, and furtherdistribution with social network providers such as Yahoo! and Facebook,ad/or the like, may be also linked to the knowledge bank database 260.In one implementation, the knowledge distributors 264 may facilitateknowledge providers 262 to access the knowledge acquirers 261 viaknowledge learning by the AI agents.

FIG. 3 provides a logic flow diagram illustrating conversation assetmonetization within embodiments of the DCM-Platform. In one embodiment,a consumer may interact with an AI agent to generate customer-AIdialogue 305. For example, in one implementation, the AI agent mayoperate an autodialer to call a consumer, wherein the audio conversationmay be recorded and the audio file may be translated into textualscripts. For another example, the AI agent may manage a social networkavatar, e.g., a messenger identity, a Facebook account, etc., and chatwith a consumer via the social network platform.

In one implementation, the AI agent may generate conversation assets bycreating a wrapper encapsulating the conversation scripts with theconsumer, as further illustrated in FIGS. 4B-4D. For example, in oneimplementation, the AI agent may convert one or more textualconversation scripts into a XML file, with metadata of the conversationscripts, such as, but not limited to ownership information, authorshipinformation, and/or the like. In one implementation, the AI agent mayassociate information such as the software implementation packages,operating system information, hardware abstraction information, with thegenerated conversation assets to generate AI entity assets 310, asfurther illustrated in FIG. 5A-5C. In an alternative implementation, theconversation assets and AI entity assets may be generated at theDCM-Platform.

Within implementations, the DCM-Platform may receive information of thegenerated conversation assets and AI entity assets and monetize theassets 313,315. For example, in one implementation, the DCM-Platform mayreceive pricing information from the owner of the assets, e.g., the AIagents, etc., and price the assets accordingly.

In one implementation, the DCM-Platform may group AI entity assets togenerate portfolio assets 318, e.g., by combining AI entity assets basedon related conversation topics, related AI entity types, and/or thelike. The generated portfolio assets may be monetized 320 for exchange,and/or grouped to generate exchange assets 325. In one implementation,the DCM-Platform may present the generated asset wrappers, including theconversation assets, AI entity assets, portfolio assets and/or exchangeassets to a financial trading platform for trade transactions 345. Inone implementation, the DCM-Platform may obtain pricing information ofthe virtual assets on the market 327, and generate a conversation index328 based on the supply-demand market characteristics. For example,conversation assets may be priced differently based on its content,topics, volume, client demands, and/or the like.

In one implementation, the DCM-Platform may adjust the conversationmonetization via monitoring the conversation index 330 in a loop 335.For example, the DCM-Platform may feedback the market prices ofconversation assets to an AI agent, which is engaged in a conversationwith a consumer and may determine a dollar value associated with adialogue step. For example, if the market information indicatesconversation assets with regard to consumer preferences over “colors ofhair highlights” are highly demanded, then during the conversation, aconsumer dialogue line “I like red hair highlights” may be priced with ahigher dollar value.

FIG. 4A provides a block diagram illustrating monetizing digital assetsbetween different entities within embodiments of the DCM-Platform.Within embodiments, digital asset owners, such as an AI agent, anadvertising company which employs AI agents for advertising services,and/or the like, may monetize their virtual assets to generate revenuesby determining and selling stock shares to investors.

For example, in one implementation, the DCM-Platform may determine acommon denominator for the exchange of value relates to theestablishment of a conversation asset, e.g., a dollar value associatedwith a dialogue script, a dialogue action/line, etc. In oneimplementation, the DCM-Platform may facilitate initiation of aconversation asset and the exchange of value between the conversationasset owner 408(a), conversation script author(s) 401(a), andconversation asset negotiator(s) 405(a), including changes over time.Within implementations, the conversation script author(s) 401(a) mayprovide conversation scripts 404(a) to the conversation asset owner(s)408(a), and the asset owner may then allocate conversation asset sharesfor negotiation 406(a), while the conversation asset negotiator 405(a)may negotiate the conversation stock transfers 407(a) via theDCM-Platform 120 to an investor 144. The example initiation ofconversation assets is further illustrated in FIGS. 4B-4D.

For another example, as further illustrated in FIGS. 5A-5C, theDCM-Platform may facilitate initiation of an AI entity asset and theexchange of value between the AI entity asset owner 408(b), AI entitydesigner(s) 401(b), and AI entity asset negotiator(s) 405(b), includingchanges over time. Within implementations, the AI entity designers401(b) may provide AI entity icons 402(b) to the AI entity assetowner(s) 408(b), and the asset owner may then allocate AI asset sharesfor negotiation 406(b), while the AI entity asset negotiator 405(a) maynegotiate the AI entity stock transfers 407(b) via the DCM-Platform 120to an investor 144.

For another example, as further illustrated in FIGS. 6A-6C, theDCM-Platform may facilitate initiation of a portfolio asset and theexchange of value between the portfolio asset owner 408(c), portfolioscript author(s) 401(c), and portfolio asset negotiator(s) 405(c),including changes over time. Within implementations, the portfolioscript author(s) 401(c) may provide portfolio scripts 404(c) to theportfolio asset owner(s) 408(c), and the asset owner may then allocateportfolio asset shares for negotiation 406(c), while the portfolio assetnegotiator 405(c) may negotiate the portfolio stock transfers 407(a) viathe DCM-Platform 120 to an investor 144.

For another example, as further illustrated in FIGS. 7A-7D, theDCM-Platform may facilitate initiation of a exchange asset and theexchange of value between the exchange asset owner 408(d), exchangescript author(s) 401(d), and exchange asset negotiator(s) 405(d),including changes over time. Within implementations, the exchange scriptauthor(s) 401(d) may provide exchange scripts 404(d) to the exchangeasset owner(s) 408(d), and the asset owner may then allocate exchangeasset shares for negotiation 406(d), while the exchange asset negotiator405(d) may negotiate the exchange stock transfers 407(d) via theDCM-Platform 120 to an investor 144.

FIGS. 4B-4D provide logic flow diagrams illustrating example initiationof a conversation asset within embodiments of the DCM-Platform.

In one embodiment, the DCM-Platform or the AI agent may create aconversation asset based on the captured conversation script. Withinimplementations, conversation assets may be created and developed 411 bythe conversation asset owner, e.g., an AI agent, an advertising company,etc., which may be a 1:1 relationship to the conversation asset. Theconversation asset owner may be an individual or an organization or anamed asset portfolio, and the ownership may be transferred to anotherperson, organization or to a named portfolio. In one implementation, anindividual name may be required as the authoritative person toestablish. Once the conversation asset owner identity and contactdetails have been established that person may create a conversationwrapper to establish the conversation asset.

In one embodiment, upon establishment of the conversation assetownership, the DCM-Platform may launch a conversation asset wrapper,which may be a data package comprising the conversation asset and tradeinformation with regard to the conversation asset, which may have a 1:1relationship to the conversation asset. Within embodiments, aconversation wrapper may be governed by a set of methods covering allthe different parts and interrelationships that are the basis foralgorithmic trading for the creation of value of a conversation asset.For example, in one implementation, an exemplar XML implementation of aconversation asset wrapper is discussed in FIG. 2B.

In one embodiment, the DCM-Platform may define a conversation assettitle 413. The conversation wrapper may contain a title of theconversation asset, which is a 1:1 relationship to the conversationasset. For example, the conversation asset owner may be responsible forthe conversation title.

In one embodiment, the DCM-Platform may allocate a unique conversationasset global identifier 414 to the conversation wrapper, which is a 1:1relationship to the conversation asset. The conversation asset globalidentifier may remain unchanged for the lifetime, including archive, ofthe conversational asset even if constitution, ownership of the assetchanges.

In one embodiment, once the conversation asset global identity has beenassigned, the conversation asset status filed in the conversationwrapper may be set 416. For example, if the conversation asset status isset to be “draft,” which is a 1:1 relationship to the conversationasset, the “draft” status may indicate the conversation asset is notready for use in a digital conversation; once the conversation assetstatus is set to be “production” then the digital conversations areready to commence.

In one embodiment, the DCM-Platform may update the conversation assetwrapper with a description of the conversation asset, which is a 1:1relationship. For example, the conversation asset owner may compile andedit the conversation description. the person responsible for theconversation description is the conversation asset owner.

In one embodiment, once the conversation description has beenestablished, the conversation asset ownership may be assigned to theconversation asset owner 417, which is a 1:1 relationship betweenconversation asset and the conversation asset owner. In oneimplementation, the establishment of ownership of the conversation assetmay determine that the conversation asset having one share, which isfully owned by the conversation asset owner. Alternative implementationsof determining shares are further illustrated in FIGS. 8A-8B.

In one embodiment, the conversation wrapper references the primaryscript author for each conversation script 418, which is a 1:1relationship. For example, the primary script may be the first componentused by an AI entity for digital conversation.

In one implementation, if the conversation asset owner is the author ofthis primary script then the primary script author identity and contactdetails are treated as the same. Otherwise, in alternativeimplementations, if the conversation asset owner is not the same as theprimary script owner then the conversation asset owner may arrange forthe following: define the primary script author identification andcontact details; ascertain whether the primary script author will begiven partial ownership of the conversation asset.

In one embodiment, upon assigning a conversation asset negotiator, theconversation asset negotiator may negotiate with the primary scriptauthor a percentage of shares to be sold and once determined the assetshares are assigned. The allocation may not be a whole unit andtherefore the assignment of conversation shares can be fractional.

In one embodiment, if both parties agree on the conversation shares thena conversation stock transfer is undertaken, where an audit trail of thetransaction is maintained as part of the conversation asset wrapper. Inone embodiment, a primary script author may be replaced by anotherprimary script author 425 and an audit trial is maintained of pastprimary script authors with the conversation wrapper. To change aprimary script author, the authority may be vested with the person withthe conversation asset negotiator. If there was a prior agreement withthe current primary script author to release their conversation sharesin the case that they loose their primary script author status then theshare allocation is removed. If there was no prior agreement the currentprimary script author may agree to release their shares in consultationwith the conversation asset negotiator. In one implementation, theshares withdrawn become part of the audit trail within the conversationasset wrapper. The primary script author may wish to retain all or partof their shares. The conversation asset negotiator may obtain prioragreement with the conversation asset owner to increase the number ofconversation shares.

In one embodiment, the conversation asset owner may ascertain whether aconversation asset negotiator is needed, e.g., a third party tonegotiate during a transaction on their behalf. In an alternativeembodiment, the conversation asset owner may be assigned the status ofconversation asset negotiator 419, which is a 1:1 relationship.

In alternative implementations, the asset owner may define conversationasset negotiator identification and contact details. For example, if theconversation asset owner wishes to assign proportional ownership to theconversation asset negotiator then a percentage is determined and theasset shares are assigned 420. The allocation may not be a whole unitand therefore the assignment of shares can be fractional, e.g., a m:mrelationship between the conversation asset shares and the conversationasset negotiator.

In one embodiment, upon negotiation the conversation asset shareallocation with the primary script author 423, and both parties agreethe conversation shares then a conversation stock transfer is undertaken421, where an audit trail of the transaction is maintained as part ofthe conversation asset wrapper. When the stock transfer is finished, theconversation asset shares are removed from the primary script author426.

In one embodiment, the DCM-Platform may determine whether there are morethan 1 primary authors. If there are other script authors, e.g., a 1:mrelationship between the conversation script and the conversationauthors 427, the conversation wrapper references the other authors foreach conversation script. In one implementation, if the conversationasset owner is an other script author, the identity and contact detailsare treated as the same. If the conversation asset owner is not the sameas one of the other script owners or if there are other script authors,then the conversation asset owner may define for each other scriptauthor identification and contact details; ascertain for each one,whether the other script author will be given partial ownership of theconversation asset.

In one embodiment, the conversation asset negotiator negotiates with theother script author 429 a percentage and once determined the assetshares are assigned and removed from other authors 430. The allocationdoes not need to be a whole unit and therefore the assignment ofconversation shares can be fractional. In one embodiment, once bothparties agree the conversation shares then a conversation stock transferis undertaken, where an audit trail of the transaction is maintained aspart of the conversation asset wrapper.

In one embodiment, conversation script rights may be assigned to otherauthors 431. An other script author may be replaced by another otherscript author and an audit trial is maintained of past other scriptauthors with the conversation wrapper. To change an other script authorthe authority is vested with the person with the conversation assetnegotiator. if there was a prior agreement with the current other scriptauthor to release their conversation shares in the case that they loosetheir other script author status then the share allocation is removed.if there was no prior agreement the current other script author mayagree to release their shares in consultation with the conversationasset negotiator. The shares withdrawn become part of the audit trailwithin the conversation asset wrapper.

In one implementation, the other script author may desire to retain allor part of their shares. The conversation asset negotiator may obtainprior agreement with the conversation asset owner to increase the numberof conversation shares. In an alternative embodiment, the other scriptauthors may not be allowed to change a script unless they have beengiven temporary authority by the primary script author. The assignmentmay be time sensitive assignment and this status may be removed. In oneimplementation, only one script author is allowed at a moment in time tochange the script.

In one embodiment, the conversation wrapper references the primaryconversation script 432, which is a 1:1 relationship wherein the primaryconversation script contains identification information such as name andversion, and/or the like.

In one embodiment, the primary conversation script may link with otherconversation scripts 433, which is a 1:m relationship and in turn eachother conversation script component may link with other conversationscripts. For example, a conversation script wrapper may reference aspecific link to another conversation script that is related to similartopics 434. These networks of conversation links are referenced from theconversation wrapper with associated creation details. The conversationscript is produced and changed by the primary script author or asalready mentioned an other script author that has been assigned thetemporary status to perform script changes. Each conversation link is toa named conversation script, which is a 1:1 relationship. Eachconversation script is a conversation asset and therefore each has itsown conversation asset owner wrappers. In one implementation, theauthorship amongst different conversation assets is likely to bedifferent. The conversation assets may be triggered by conversationlinks that potentially increase the value of the conversation asset,which is described within the conversation wrapper.

In one embodiment, the conversation wrapper references for each scriptauthor their bio in context of the conversation script 435, which is a1:1 relationship.

In one embodiment, the conversation may orchestrate one ore moredialogue steps 436; a conversation step may orchestrate one or moreactivities, which is a 1:m relationship. Within implementations, theconversation orchestration handles three primary activities, which areevents, widgets and adverts.

In one implementation, the conversational orchestration may trigger oneor more events 437, which is a 1:m relationship. These conversationevents are in context to the conversation step and thus cover thingssuch as an AI entity movement to the trigger of any digital medium suchas an audio, picture, video or indeed any digital medium. Those digitalmediums triggered by conversation assets that potentially increase thevalue of the conversation asset may be described within the conversationwrapper. For example, a conversational event may comprise, but notlimited to transmission of a multimedia file (e.g., an audio, video,etc.) in a text based dialogue, consumer's election to switch AI agentsduring a conversation, and/or the like.

In one embodiment, the conversational orchestration may trigger one ormore widgets 438, which is a 1:m relationship. These conversationwidgets are in context to the conversation step and thus cover any typeof function that may be performed by a widget such as a diaryappointment to a transaction, e.g., a scheduled transfer of stockshares. Those conversation widgets triggered by conversationorchestration that potentially increase the value of the conversationasset may be described within the conversation wrapper.

In one embodiment, the conversational orchestration may trigger one ormore adverts 439, which is a 1:m relationship. The advert may coverdifferent forms such as a pictorial or video. These conversation advertsare in context to the conversation step and are governed by the methodsfor exchanging value for advertisements. These conversation adverts maybe undertaken in conjunction with conversation events and conversationwidgets. Those conversation adverts triggered by conversationorchestration that potentially increase the value of the conversationasset may be described within the conversation wrapper. For example, thelink to the conversational advert may be date and time sensitive andthus enabling different placements for different contexts.

In one embodiment, the conversation wrapper may be used to recommendother conversation assets. For example, the conversation wrapper maydetermine link references to other conversation through the file wrapper440, which may further involve the trading of conversation asset sharesor the assignment of conversation asset shares new shares between therespective conversation asset negotiators 441.

FIGS. 5A-5C provide logic flow diagrams illustrating monetizing an AIentity asset within embodiments of the DCM-platform. In one embodiment,the AI entity is a logical and/or physical form of artificialintelligence that is used as the conduit of a digital conversation,e.g., it may be an avatar whereas in a physical form it may be say ahousehold robot, an autodialing system, a virtual identity on amessenger/social media platform, etc. In one implementation, in itslogical form a digital conversation is used for dialogue but may alsogovern movement of the AI entity or instruct the AI entity to perform atask.

Within implementations, the AI entity asset may be treated in a similarway to a conversation asset. In one embodiment, the conversation AIentity asset is created and developed by the conversation AI entityasset owner, which is a 1:1 relationship 511. The conversation AI entityasset owner may be an individual or an organization or a namedportfolio, however, if the latter two then an individual name may berequired as the authoritative person. The ownership may change toanother person, organization or to a named portfolio. Once theconversation AI entity asset owner identity and contact details havebeen established that person may create a conversation AI entity wrapperto establish the conversation AI entity asset.

In one embodiment, each conversation AI entity asset may launch an AIentity asset wrapper 512, which has a 1:1 relationship. In oneimplementation, a conversation AI entity wrapper is governed by a set ofmethods covering all the different parts and interrelationships that arethe basis for algorithmic trading for the creation of value of aconversation AI entity asset, which may be traded as a tangible andmeasurable financial instrument.

In one embodiment, the conversation AI entity wrapper may contain a nameof the conversation AI entity asset 513, which is a 1:1 relationship.For example, the conversation AI entity asset owner may be responsiblefor the conversation AI entity name.

In one embodiment, once the conversation name has been established, aunique global identifier is assigned to the conversation AI entitywrapper 514, which is a 1:1 relationship. The conversation AI entityasset global identifier may remain unchanged for the lifetime, includingarchive, of the conversational AI entity asset even if the constitutionof the asset changes.

In one embodiment, once the AI entity asset global identifier has beenestablished, the conversation AI entity asset ownership may be fullyassigned to the conversation AI entity asset owner 515. Withinimplementations, there may be a 1:1 relationship between conversation AIentity asset and the conversation AI entity asset owner, which mayindicate that the conversation AI entity asset has one share, fullyowned by the conversation AI entity asset owner.

In one embodiment, the conversation AI entity asset owner may ascertainwhether they wish someone else to negotiate on their behalf. In oneimplementation, the conversation AI entity asset owner is assigned thestatus of conversation AI entity asset negotiator 516, which is a 1:1relationship.

In alternative implementations, the conversation AI entity asset maydefine conversation AI entity asset negotiator identification andcontact details 521. In one embodiment, if the conversation AI entityasset owner wishes to assign proportional ownership to the conversationAI entity asset negotiator, then a percentage is determined and theconversation AI entity shares are assigned 522. The allocation may notbe a whole unit and therefore the assignment of shares may befractional.

In one embodiment, once both parties agree the conversation AI entityshares then a conversation AI entity stock transfer is undertaken, wherean audit trail of the transaction is maintained as part of theconversation AI entity wrapper.

In one embodiment, the conversation AI entity wrapper references theprimary AI entity designer for each AI entity design 517, which is a 1:1relationship. If the conversation AI entity asset owner is the maindesigner then the primary AI entity designer identity and contactdetails are treated as the same. If the conversation AI entity assetowner is not the same as the primary AI entity designer then theconversation AI entity asset owner may define the primary AI entitydesigner identification and contact details; and ascertain whether theprimary AI entity designer will be given partial ownership of theconversation AI entity asset. if so, the conversation AI entity assetnegotiator may negotiate with the primary AI entity designer apercentage and once determined the AI entity shares are assigned 518.the allocation may not be a whole unit and therefore the assignment ofAI entity shares may be fractional.

In one embodiment, once both parties agree the AI entity shares then aconversation AI entity stock transfer is undertaken 519, where an audittrail of the transaction is maintained as part of the conversation AIentity asset wrapper 520.

In one embodiment, a primary AI entity designer may be replaced byanother primary AI entity designer 523 and an audit trial is maintainedof past primary AI entity designers with the conversation AI entitywrapper. To change a primary AI entity designer, the authority may bevested with the person with the conversation AI entity asset negotiatorstatus. if there was a prior agreement with the current primary AIentity designer to release their conversation AI entity shares in casethat they lose their primary AI entity designer status, then the shareallocation is removed 524. if there was no prior agreement, the currentprimary AI entity designer may agree to release their shares inconsultation with the conversation AI entity asset negotiator. Theshares withdrawn become part of the audit trail within the conversationAI entity asset wrapper. The primary AI entity designer may wish toretain all or part of their shares. The conversation AI entity assetnegotiator may obtain prior agreement with the conversation AI entityasset owner to increase the number of conversation AI entity shares.

In one embodiment, there may be more than one AI entity designer 525,which is a 1:m relationship. Within implementations, the conversation AIentity wrapper references the other designers for each separate designfor the same AI entity, which is a 1:m relationship. The conversation AIentity asset owner may be an other AI entity designers and if so theidentity and contact details are treated as the same. If theconversation AI entity asset owner is not the same as one of the otherAI entity designers or if there is a need for one other AI entitydesigner then the conversation AI, entity asset owner may: define foreach other AI entity designer identification and contact details;ascertain for each one, whether the other AI entity designer will begiven partial ownership of the conversation AI entity asset. if so, theconversation AI entity asset negotiator may negotiates with the other AIentity designer 527 a percentage and once determined the conversation AIentity shares are assigned 529, and the AI entity asset shares areremoved 528. The allocation may not be a whole unit and therefore theassignment of conversation AI entity shares may be fractional.

In one embodiment, once both parties agree the conversation AI entityshares then a conversation stock transfer is undertaken, where an audittrail of the transaction is maintained as part of the conversation AIentity asset wrapper.

In one embodiment, an other AI entity designer may be replaced byanother other AI entity designer and an audit trial is maintained ofpast other AI entity designer with the conversation AI entity wrapper.To change an other AI entity designer the authority may be vested withthe person with the conversation AI entity asset negotiator. If therewas a prior agreement with the current other AI entity designer torelease their conversation AI entity shares in the case that they loosetheir other AI entity designer status then the share allocation isremoved. If there was no prior agreement the current other AI entitydesigner may agree to release their shares in consultation with theconversation AI entity asset negotiator. The shares withdrawn becomepart of the audit trail within the conversation AI entity asset wrapper.The other AI entity designer may wish to retain all or part of theirshares. The conversation AI entity asset negotiator may obtain prioragreement with the conversation AI entity asset owner to increase thenumber of conversation shares.

In one embodiment, the other AI entity designers are not allowed tochange a design unless they have been given temporary authority by theprimary AI entity designer. This may be a time sensitive assignment andthis status may be removed. In one implementation, only one AI entitydesigner is allowed at a moment in time to change the design.

In one embodiment, the conversation AI entity wrapper references theprimary AI entity icon 530 defined by AI entity designers, which is a1:1 relationship. This primary AI entity icon contains identificationinformation such as name and version. Within implementations, theprimary AI entity icon may have a primary AI entity design and may haveany number of other AI entity icon designers.

In one embodiment, the AI entity icon references within the conversationAI entity wrapper other AI entity icons 533, which is a 1:mrelationship. For example, different representations may be needed fordifferent devices within the AI entity. Each variation containsidentification information such as name and version.

In one embodiment, the conversation AI entity icon orchestrates specificconversation scripts, including a list of different conversations to theAI entity 534, which is a 1:m relationship, which means the same AIentity icon may engage in a range of different scripted digitalconversations. Each orchestrated scripted conversation is uniquelyidentified, which includes the name and descriptions. These conversationscripts may link with other components of conversation script, which isa 1:m relationship and in turn each other conversation script componentmay link with other conversation script components. These networks ofconversation links are referenced from the conversation wrapper withassociated creation details. Within implementations, some AI entitiesmay become labeled as “good” conversation and thus increase the value ofthe AI entity itself as it develops brand value. The conversation AIentity wrapper may contain a list of the conversation scripts associatedwith the AI entity 534.

In one embodiment, the conversation wrapper references for each AIEntity Designer their bio in context of the AI Entity Icon 535, which isa 1:1 relationship.

In one embodiment, an AI Entity may orchestrate activities based ondialogue-steps within digital conversations 536, which is a 1:mrelationship. The AI Entity orchestration handles three primaryactivities, which are events, widgets and adverts.

In one embodiment, the AI Entity orchestration may trigger one or moreevents 537, which is a 1:m relationship. These conversation AI entityevents are in context to the conversation step and thus cover thingssuch as an AI entity movement to the trigger of any digital medium suchas an audio, picture, video or indeed any digital medium. Those digitalmediums triggered by AI entities potentially increase the value of theconversation AI entity asset may be described within the conversation AIentity wrapper.

In one embodiment, the AI entity orchestration may trigger one or morewidgets 538, which is a 1:m relationship^(d2,28). These conversation AIentity widgets are in context to the conversation step and thus coverany type of function that may be performed by a widget such as a diaryappointment to a transaction. Those widgets triggered by AI entityorchestration that potentially increase the value of the conversation AIentity asset may be described within the conversation AI entity wrapper.

In one embodiment, the AI entity orchestration may trigger one or moreadverts 539, which is a 1:m relationship. The advert may cover differentforms such as a pictorial or video. these conversation adverts are incontext to the conversation step and are governed by the methods forexchanging value for advertisements. These conversation AI entityadverts may be undertaken in conjunction with conversation AI entityevents and conversation AI entity widgets. Those conversation AI entitywidgets triggered by AI entity orchestration that potentially increasethe value of the conversation AI entity asset can be described withinthe conversation AI entity wrapper. the link to the conversational AIentity advert may be date and time sensitive and thus enabling differentplacements for different contexts. The link to the conversational AIentity advert may be data sensitive and thus enabling differentplacements for different contexts.

In one embodiment, the AI entity icon may contain a 3^(rd) party brandor brands as part of its inventory 540, this is a 1:m relationship. Thevalue of this brand displayed is influenced by a number of factors,including the volume of dialogue steps. This AI entity brand display maybe date and time sensitive and thus enabling different placements fordifferent contexts. The conversational AI entity brand display may bedata sensitive and thus enabling different placements for differentcontexts.

In one embodiment, the conversation wrapper may be used to recommendother conversation AI entity asset, including link references to otherAI entities through wrapper 541. This may involve the trading ofconversation AI entity asset shares or the assignment of conversation AIentity asset shares new shares between the respective conversation AIentity asset negotiators.

In one embodiment, once the conversation AI entity asset global identityhas been assigned, the conversation wrapper is mandated with theconversation AI entity asset status 542, e.g., set to “draft,” which isa 1:1 relationship. The “draft” status may indicate the conversation AIentity asset is not ready for digital conversation interaction, while a“production” status may indicate the digital conversations through theAI entity icon are ready to commence.

In one embodiment, the DCM-Platform may facilitate negotiate sharetransfers between different AI entities 543 in a similar manner asdiscussed in FIGS. 5A-5C.

FIGS. 6A-6C provide logic flow diagrams illustrating monetizing aportfolio asset within embodiments of the DCM-Platform. In oneembodiment, the portfolio conversation asset is the aggregation ofconversation assets and AI entity assets that it has accredited, whereina portfolio conversation asset's overall value will be determined byfactors such as its brand and what it represents in terms of digitalconversation. In one implementation, the portfolio conversation assetmay be treated in a similar way to a conversation asset or as aconversation AI entity asset.

In one embodiment, the portfolio conversation asset is created anddeveloped by the portfolio conversation asset owner 611, which is a 1:1relationship. The portfolio conversation asset owner may be anindividual or an organization, wherein the latter may require anindividual name as the authoritative person. This ownership can changeto another person, organization or to a named portfolio. Once theportfolio conversation asset owner identity and contact details havebeen established, the owner may create a portfolio conversation wrapperto establish the portfolio conversation asset.

In one embodiment, each portfolio conversation asset may launch awrapper 612, which has a 1:1 relationship. A portfolio conversationwrapper is governed by a set of methods covering all the different partsand interrelationships that are the basis for algorithmic trading forthe creation of value of a portfolio conversation asset. In oneimplementation, a portfolio conversation asset may be traded in digitalform as a tangible and measurable financial instrument.

In one embodiment, the portfolio conversation wrapper may contain atitle of the portfolio conversation asset 613, which is a 1:1relationship. In one implementation, the asset owner may be responsiblefor the portfolio conversation title, which may be followed by aportfolio conversation asset description.

In one embodiment, once the portfolio conversation title has beenestablished, a unique global identifier is assigned to the portfolioconversation wrapper 614, which is a 1:1 relationship. The portfolioconversation asset global identifier may remain unchanged for thelifetime, including archive, of the conversational portfolioconversation asset even if the constitution of the asset changes.

In one embodiment, once the portfolio conversation asset globalidentifier has been established, the portfolio conversation assetownership is fully assigned to the portfolio conversation asset owner615, with a 1:1 relationship between the portfolio conversation assetand the portfolio conversation asset owner, which may indicate theportfolio conversation asset has one share, fully owned by the portfolioconversation asset owner.

In one embodiment, the portfolio conversation asset owner may ascertainwhether they wish someone else to negotiate on their behalf. If not, theportfolio conversation asset owner is assigned the status of portfolioconversation asset negotiator. Otherwise it may assign one or more otherpeople to the status portfolio conversation asset negotiator 616, whichis a 1:m relationship; in other words, a portfolio may consist of anynumber of portfolio conversation asset negotiators thus enabling theportfolio to grow to any size it wishes.

In one implementation, the portfolio asset owner may retain the right tobe a portfolio conversation asset negotiator but also communicate with,and/or require participations of other portfolio conversation assetnegotiators. To establish one or more other portfolio conversation assetnegotiators, the owner may define portfolio conversation assetnegotiator identification and contact details. The portfolioconversation asset negotiator may become a member of the portfolioconversation asset 618.

In one implementation, if the portfolio conversation asset owner wishesto assign proportional ownership to the portfolio conversation assetnegotiator then a percentage is determined and the portfolioconversation shares are assigned 617. The allocation may not be a wholeunit and therefore the assignment of shares can be fractional. Withinimplementations, once both parties agree the portfolio conversationshares then a portfolio conversation stock transfer is undertaken 619,where an audit trail of the transaction is maintained as part of theportfolio conversation wrapper 620.

In one embodiment, the portfolio conversation wrapper references theportfolio conversation member or members that cover the spectrum foreach conversation asset or conversation AI entity asset, which is a 1:mrelationship. The method for engaging new portfolio conversation membersmay be undertaken by the portfolio conversation asset negotiator. Forexample, the asset negotiator may define the portfolio conversationmember identification and contact details; ascertain whether theportfolio conversation member will be given partial ownership of theportfolio conversation asset. if so, then in one embodiment, theportfolio conversation asset negotiator negotiates with the portfolioconversation member 621 a percentage and once determined the portfolioconversation shares are assigned 622. The allocation may not a wholeunit and therefore the assignment of portfolio conversation shares canbe fractional.

In one embodiment, once both parties agree the portfolio conversationshares then a portfolio conversation stock transfer is undertaken, wherean audit trail of the transaction is maintained as part of the portfolioconversation asset wrapper.

In one embodiment, a portfolio conversation member may be replaced byanother portfolio conversation member 644 and an audit trial ismaintained of past portfolio conversation members within the portfolioconversation wrapper. To change a portfolio conversation member theauthority may be vested with the person with the portfolio conversationasset negotiator status. If there was a prior agreement with the currentportfolio conversation member to release their portfolio conversationshares in the case that they loose their portfolio conversation memberstatus then the share allocation is removed 624. If there was no prioragreement the current portfolio conversation member may agree to releasetheir shares in consultation with the portfolio conversation assetnegotiator. The shares withdrawn become part of the audit trail withinthe portfolio conversation asset wrapper. The portfolio conversationmember may wish to retain all or part of their shares. The portfolioconversation asset negotiator may obtain prior agreement with theportfolio conversation asset owner to increase the number of portfolioconversation shares.

In one embodiment, a portfolio conversation member may be assigned, ifagreeable, the status of Reviewer 623, which is a role for the portfolioconversation member to have the vested authority to review conversationassets and conversation AI entity assets. There may be multipleportfolio conversation reviewers, which is a 1:1 relationship withportfolio conversation member. A portfolio conversation reviewer may notreview conversation assets and conversation AI entity assets that theyhave authored or designed respectively. In one implementation, theportfolio conversation wrapper references portfolio conversationreviewers 625. For each portfolio conversation reviewer, the wrapper mayreference a description of their relevant experience, and the assetowner may ascertain whether the portfolio conversation reviewer will begiven partial ownership of the portfolio conversation asset in exchangefor their contribution to reviews. If so, then in one embodiment, theportfolio conversation asset negotiator negotiates with the portfolioconversation reviewer a percentage and once determined the portfolioconversation shares are assigned. The allocation may not be a whole unitand therefore the assignment of portfolio conversation shares can befractional.

In one embodiment, once both parties agree the portfolio conversationshares then a conversation stock transfer is undertaken, where an audittrail of the transaction is maintained as part of the portfolioconversation asset wrapper.

In one embodiment, the portfolio conversation reviewer status can beremoved 626, e.g., when the portfolio conversation negotiator isinvolved and then the change of status defined on the portfolioconversation wrapper. An audit trial is maintained of past portfolioconversation reviewers within the portfolio conversation wrapper. Ifthere was a prior agreement with the portfolio conversation reviewer torelease their portfolio conversation shares in the case that they loosetheir portfolio conversation reviewer status then the share allocationis removed. If there was no prior agreement, the current portfolioconversation reviewer may agree to release their shares in consultationwith the portfolio conversation asset negotiator. The shares withdrawnbecome part of the audit trail within the portfolio conversation assetwrapper. The portfolio conversation reviewer may retain all or part oftheir shares. In one embodiment, the portfolio conversation reviewer maynot have the authority to change a conversation asset or a conversationAI entity asset.

In one embodiment, a portfolio conversation member may be assigned, ifagreeable, the status of accreditor, which may be a role for theportfolio conversation member to have the vested authority to provide anaccreditation rating for conversation assets and conversation AI entityassets. Within implementations, there can be multiple portfolioconversation accreditors, which is a 1:1 relationship with portfolioconversation member. A portfolio conversation accreditor can also be aportfolio conversation reviewer, subject to the rules established by theportfolio conversation owner.

In one implementation, a portfolio conversation accreditor may notaccredit conversation assets and conversation AI entity assets that theyhave authored or designed respectively. The portfolio conversationwrapper references portfolio conversation accreditors. For eachportfolio conversation accreditor, the wrapper may contain a descriptionof their relevant experience, and the owner may ascertain whether theportfolio conversation accreditor will be given partial ownership of theportfolio conversation asset in exchange for their contribution toaccreditation ratings. If so, in one embodiment, the portfolioconversation asset negotiator negotiates with the portfolio conversationaccreditor a percentage and once determined the portfolio conversationshares are assigned. The allocation does not need to be a whole unit andtherefore the assignment of portfolio conversation shares can befractional.

In one embodiment, once both parties agree the portfolio conversationshares then a conversation stock transfer is undertaken, where an audittrail of the transaction is maintained as part of the portfolioconversation asset wrapper.

In one embodiment, the portfolio conversation accreditor status can beremoved 627. For example, the portfolio conversation negotiator mayremove the accreditor status and involves notification and then thechange of status defined on the portfolio conversation wrapper. An audittrial is maintained of past portfolio conversation accreditors withinthe portfolio conversation wrapper. If there was a prior agreement withthe portfolio conversation accreditor to release their portfolioconversation shares in the case that they loose their portfolioconversation accreditor status then the share allocation is removed 628.If there was no prior agreement the current portfolio conversationaccreditor may agree to release their shares in consultation with theportfolio conversation asset negotiator. The shares withdrawn becomepart of the audit trail within the portfolio conversation asset wrapper.

In one embodiment, the portfolio conversation accreditor may not havethe authority to change a conversation asset or a conversation AI entityasset.

In one embodiment, the portfolio conversation negotiator may removeshares 628, which belong to a member. This may be addressed by theportfolio conversation negotiator and involves notification and then theremoval of portfolio conversation asset shares, which requires an updateto the portfolio conversation wrapper. An audit trial is maintained ofremoved shares within the portfolio conversation wrapper.

In one embodiment, the portfolio conversation wrapper references theportfolio conversation brand 629, which is a 1:1 relationship. In oneimplementation, the portfolio conversation asset owner is responsiblefor changes to the portfolio conversation asset brand. An audit trial ismaintained of changes to the portfolio conversation asset brand withinthe portfolio conversation wrapper.

In one embodiment, the portfolio conversation wrapper references eachconversation asset 630, which is a 1:m relationship. The conversationasset may be developed by portfolio conversation members within theportfolio conversation. In another embodiment, for conversation assetsdeveloped outside the domain of the portfolio, the conversation assetauthor may wish to become a member of the portfolio so that theirconversation assets can be reviewed and receive an accreditation rating.The portfolio conversation owner through their portfolio conversationnegotiator may require that they take ownership of conversation assetshares. In this case, the negotiations may be undertaken between theportfolio conversation negotiator and the conversation asset negotiator,and ascertain the value of exchange in terms of shares.

In one implementation, there may be an agreement of new shares withinthe conversation asset that are assigned to the portfolio conversationasset. In other words, the agreed transfer of conversation asset sharesis registered with the portfolio conversation wrapper.

In one embodiment, the negotiation may involve a swap of shares betweenthe portfolio conversation asset and the conversation asset. Theconversation asset negotiator may agree to pay an amount that may bestandalone or in conjunction with the trade in shares as described. Ifthe amount, is agreed then this transaction may be entered in theportfolio conversation monetization log with all the transactionaldetails.

Once the portfolio conversation asset negotiator agrees the valueexchange terms with the conversation asset negotiator then thetransaction is completed, which may include assignment of conversationasset shares and if necessary portfolio conversation asset shares, whichare stored in their respective wrappers. The allocations may not be awhole unit and therefore the assignment of conversation shares may befractional.

In one embodiment, once both parties agree the shares then a stocktransfer is undertaken with an audit trail of the transactionsmaintained on the respective wrappers for the portfolio conversationasset and the conversation asset.

In one embodiment, the portfolio conversation wrapper contains a list ofall conversation asset shares and a link to the conversation asset andits wrapper, which is then eligible for receiving the portfolio assetbrand and subsequent portfolio reviews and accreditation.

In one embodiment, the conversation asset wrapper contains a list of allportfolio conversation asset shares within its wrapper. Withinimplementations, the conversation asset may be exclusive or nonexclusive with a portfolio conversation asset. if it is the latter, thenthe conversation asset may be represented by any number of portfolios.

In one embodiment, the portfolio conversation wrapper references eachconversation AI entity asset 631 to the portfolio, which is a 1:mrelationship. The conversation AI entity asset may be developed byportfolio conversation members within the portfolio conversation, andtherefore follows the methods as already defined for Conversation AIEntity Assets. In other implementations, for conversation AI entityassets developed outside the domain of the portfolio, the conversationAI entity designer may wish to become a member of the portfolio so thattheir conversation AI entity assets can be reviewed and receive anaccreditation rating. In order to do so, the portfolio conversationowner through their portfolio conversation negotiator may require thatthey take ownership of conversation AI entity asset shares. In thiscase, the negotiations may be undertaken between the portfolioconversation negotiator and the conversation AI entity asset negotiator.

In one implementation, the portfolio asset owner may ascertain the valueof exchange in terms of shares. In one embodiment, this may be anagreement of net shares within the conversation AI entity asset that areassigned to the Portfolio conversation asset. In other words, the agreedtransfer of conversation AI entity asset shares may be registered withthe portfolio conversation wrapper.

In one embodiment, the negotiation may involve a swap of shares betweenthe portfolio conversation asset and the conversation AI entity asset.In one embodiment, the negotiator may agree to pay an amount that may bestandalone or in conjunction with the trade in shares as described. Ifthe amount is agreed then this transaction may be entered in theportfolio conversation monetization log with all the transactionaldetails.

In one embodiment, once the portfolio conversation asset negotiatoragrees the value exchange terms with the conversation AI entity assetnegotiator then the transaction is completed. This includes assignmentof conversation AI entity asset shares and if necessary portfolioconversation asset shares, which are stored in the respective wrappers.The allocations may not be a whole unit and therefore the assignment ofshares can be fractional.

In one embodiment, once both parties agree the shares then a stocktransfer is undertaken with an audit trail of the transactionsmaintained on the respective wrappers for the portfolio conversationasset and the conversation AI entity asset.

In one embodiment, the portfolio conversation wrapper contains a list ofall conversation AI entity asset shares and a link to the conversationAI entity asset and its wrapper, which is then eligible for receivingthe portfolio asset brand and subsequent portfolio reviews andaccreditation.

In one embodiment, the conversation AI entity asset wrapper contains alist of all portfolio conversation asset shares within its wrapper.Within implementations, the conversation AI entity asset may beexclusive or non exclusive with a portfolio conversation asset. if it isthe latter, then the conversation AI entity asset may be represented byany number of portfolios.

In one embodiment, the portfolio conversation wrapper references foreach portfolio conversation member their bio 632, which is a 1:1relationship.

In one embodiment, a portfolio conversation wrapper may maintain acounter of the dialogue-steps within digital conversations 633, which isa 1:m relationship for each conversation asset.

In one embodiment, a portfolio conversation wrapper maintains a counterof the conversation asset events 634 triggered by digital conversations,which is a 1:m relationship for each conversation asset.

In one embodiment, a portfolio conversation wrapper maintains a counterof the conversation asset widgets 635 triggered by digitalconversations, which is a 1:m relationship for each conversation asset.

In one embodiment, a portfolio conversation wrapper maintains a counterof the conversation asset adverts 636 triggered by digitalconversations, which is a 1:m relationship for each conversation asset.

In one embodiment, a portfolio conversation wrapper maintains a counterof the conversation asset web-services 637 triggered by digitalconversations, which is a 1:m relationship for each conversation asset.

In one embodiment, a portfolio conversation wrapper maintains a counterof the conversation AI entity brand displays (3^(rd) Party) 638triggered by digital conversations, which is a 1:m relationship for eachconversation AI entity asset.

In one embodiment, all interactions and transactions related to theportfolio conversation asset are stored as an audit that provides abasis for future projected value 639. This audit history is accessiblefrom the portfolio conversation wrapper, which is a 1:m relationship.

In one embodiment, a portfolio conversation wrapper maintains a list ofportfolio conversation members that also have the status of portfolioconversation authors 640, which is a 1:m relationship in a similarmanner as discussed in establishing conversation asset authors.

In one embodiment, a portfolio conversation wrapper maintains a list ofportfolio conversation members that also have the status of portfolioconversation designers 641, which is a 1:m relationship. The means tobecome a designer is covered in the methods associated with conversationAI entity designer.

In one embodiment, the portfolio conversation wrapper may be used toestablish references 642 for other portfolio conversation assets, whichmay include the trading of portfolio conversation asset shares or theassignment of portfolio conversation asset shares, and/or new shares 645between the respective portfolio conversation asset negotiators.

FIGS. 7A-7D provide logic flow diagrams illustrating monetizing anexchange asset within embodiments of the DCM-Platform. In oneembodiment, the exchange conversation asset is the aggregation ofconversation assets and AI entity assets that have been accredited bythe portfolio conversation asset that has a relationship with theexchange conversation asset. An exchange conversation asset's overallvalue will be determined by factors such as its brand and what itrepresents in terms of digital conversation from the aggregation ofportfolio conversation assets. The exchange conversation asset istreated in a similar way to a portfolio conversation asset, withdifferent embodiments in trading conversation assets and conversation AIentity assets. The exchange conversation asset may have its ownportfolio conversation asset to directly deal with conversation authorsand conversation AI entity designers that are not exclusive to otherportfolio conversation assets. The exchange conversation asset may belinked with multiple exchange conversation assets.

In one embodiment, the exchange conversation asset is created anddeveloped by the exchange conversation asset owner 711, which is a 1:1relationship. The exchange conversation asset owner may be an individualor an organization, wherein an individual name may be needed as theauthoritative person. This ownership can change to another individual oranother organization. In one implementation, once the exchangeconversation asset owner identity and contact details have beenestablished that person may create an exchange conversation wrapper 712to establish the exchange conversation asset.

In one embodiment, each exchange conversation asset contains a wrapper712, which has a 1:1 relationship. An exchange conversation wrapper isgoverned by a set of methods covering all the different parts andinterrelationships that are the basis for algorithmic trading for thecreation of value of an Exchange Conversation Asset. In oneimplementation, the exchange conversation asset is tradable in digitalforms as a financial instrument.

In one embodiment, the exchange conversation wrapper may contain a titleof the Exchange Conversation Asset 713, which is a 1:1relationship^(D4,3). The exchange conversation asset owner person may beresponsible for the exchange conversation title, followed by an exchangeconversation asset description.

In one embodiment, once the exchange conversation title has beenestablished, a unique global identifier is assigned to the exchangeconversation wrapper 714, which is a 1:1 relationship. The exchangeconversation asset global identifier may remain unchanged for thelifetime, including archive, of the conversational exchange conversationasset even if the constitution of the asset changes.

In one embodiment, once the exchange conversation asset globalidentifier has been established the exchange conversation assetownership is fully assigned to the exchange conversation asset owner715, with a 1:1 relationship between the exchange conversation asset andthe exchange conversation asset owner. This is equivalent to theexchange conversation asset having one share, which is fully owned bythe exchange conversation asset owner.

In one embodiment, the exchange conversation asset owner may ascertainwhether they wish someone else to negotiate on their behalf 716. if not,the exchange conversation asset owner is assigned the status of exchangeconversation asset negotiator. Otherwise it may assign one or more otherpeople to the status exchange conversation asset negotiator 716, whichis a 1:m relationship; in other words, an exchange may consist of anynumber of exchange conversation asset negotiators thus enabling theexchange to grow to any size it wishes. The exchange asset owner mayretain the right to be an exchange conversation asset negotiator, butalso require more exchange conversation asset negotiators. To establishone or more other exchange conversation asset negotiators, the assetowner may define exchange conversation asset negotiator identificationand contact details. The exchange conversation asset negotiator becomesa member of the exchange conversation asset.

In one embodiment, if the exchange conversation asset owner wishes toassign proportional ownership to the exchange conversation assetnegotiator then a percentage is determined and the exchange conversationshares are assigned 717. The allocation may not be a whole unit andtherefore the assignment of shares can be fractional.

In one embodiment, once both parties agree the exchange conversationshares then an exchange conversation stock transfer 719 is undertaken,where an audit trail of the transaction is maintained as part of theexchange conversation wrapper.

In one embodiment, the exchange conversation wrapper references theexchange conversation member or members that cover the spectrum for eachconversation asset or conversation AI entity asset within each portfolioconversation asset 718, which is a 1:m relationship. The method forengaging new Exchange conversation members may be undertaken by theexchange conversation asset negotiator as follows.

In one implementation, the asset owner may define the exchangeconversation member identification and contact details; ascertainwhether the exchange conversation member will be given partial ownershipof the exchange conversation asset. If so, then the exchangeconversation asset negotiator negotiates 721 with the exchangeconversation member a percentage and once determined the exchangeconversation shares are assigned 722. The allocation may not be a wholeunit and therefore the assignment of exchange conversation shares can befractional. In one embodiment, once both parties agree the exchangeconversation shares then an exchange conversation stock transfer isundertaken 719, where an audit trail of the transaction is maintained aspart of the exchange conversation asset wrapper 720.

In one embodiment, an exchange conversation member can be replaced byanother exchange conversation member and an audit trial is maintained ofpast exchange conversation members within the exchange conversationwrapper. To change an exchange conversation member, the authority may bevested with the person with the exchange conversation asset negotiatorstatus. If there was a prior agreement with the current exchangeconversation member to release their exchange conversation shares in thecase that they loose their exchange conversation member status then theshare allocation is removed 724. If there was no prior agreement thecurrent exchange conversation member may agree to release their sharesin consultation with the exchange conversation asset negotiator. Theshares withdrawn become part of the audit trail within the exchangeconversation asset wrapper. The exchange conversation member may wish toretain all or part of their shares. The exchange conversation assetnegotiator may obtain prior agreement with the exchange conversationasset owner to increase the number of exchange conversation shares.

In one embodiment, an exchange conversation member may be assigned, ifagreeable, the status of reviewer 723, which may be a role for theexchange conversation member to have the vested authority to reviewportfolio conversation assets, conversation assets and conversation AIentity assets. There may be multiple exchange conversation reviewers,which is a 1:1 relationship with exchange conversation member. Anexchange conversation reviewer may not review conversation assets andconversation AI entity assets that they have authored or designedrespectively. In one implementation, it is optional for the exchange toreview conversation assets and conversation AI entity assets, which maybe undertaken to increase the future earnings of an asset. The exchangeconversation wrapper references exchange conversation reviewers. Foreach exchange conversation reviewer, the wrapper may include adescription of their relevant experience, and ascertain whether theexchange conversation reviewer will be given partial ownership of theexchange conversation asset in exchange for their contribution toreviews. If so, then the exchange conversation asset negotiatornegotiates with the exchange conversation reviewer a percentage and oncedetermined the exchange conversation shares are assigned. The allocationmay not be a whole unit and therefore the assignment of ExchangeConversation Shares can be fractional.

In one embodiment, once both parties agree the exchange conversationshares then a conversation stock transfer is undertaken, where an audittrail of the transaction is maintained as part of the exchangeconversation asset wrapper.

In one embodiment, the exchange conversation reviewer status may beremoved 726. For example, the removal may be addressed by the exchangeconversation negotiator and involves notification and then the change ofstatus defined on the exchange conversation wrapper. An audit trial ismaintained of past exchange conversation reviewers within the exchangeconversation wrapper. If there was a prior agreement with the exchangeconversation reviewer to release their exchange conversation shares inthe case that they loose their exchange conversation reviewer statusthen the share allocation is removed. If there was no prior agreementthe current exchange conversation reviewer may agree to release theirshares in consultation with the exchange conversation asset negotiator.The shares withdrawn become part of the audit trail within the exchangeconversation asset wrapper. The exchange conversation reviewer may wishto retain all or part of their shares.

In one embodiment, the exchange conversation reviewer may not have theauthority to change a portfolio conversation asset, conversation assetor a conversation AI entity asset.

In one embodiment, an exchange conversation member may be assigned, ifagreeable, the status of accreditor 725, which is a role for theexchange conversation member to have the vested authority to provide anaccreditation rating for portfolio conversation assets, conversationassets and conversation AI entity assets. There may be multiple exchangeconversation accreditors, which is a 1:1 relationship with the exchangeconversation member. An exchange conversation accreditor can also be anexchange conversation reviewer, subject to the rules established by theexchange conversation owner. An exchange conversation accreditor may notaccredit conversation assets and conversation AI entity assets that theyhave authored or designed respectively nor can they accredit a portfolioconversation asset that they hold the status of conversation asset owneror conversation asset negotiator. The exchange conversation wrapperreferences exchange conversation accreditors. For each exchangeconversation accreditor, the wrapper may include a description of theirrelevant experience, and ascertain whether the exchange conversationaccreditor will be given partial ownership of the exchange conversationasset in exchange for their contribution to accreditation ratings. Ifso, then the exchange conversation asset negotiator negotiates^(d4,11)with the exchange conversation accreditor a percentage and oncedetermined the exchange conversation shares are assigned. The allocationmay not need to be a whole unit and therefore the assignment of exchangeconversation shares can be fractional.

In one embodiment, once both parties agree the exchange conversationshares then a conversation stock transfer is undertaken, where an audittrail of the transaction is maintained as part of the exchangeconversation asset wrapper.

In one embodiment, the exchange conversation accreditor status may beremoved 727. For example, the removal may be addressed by the exchangeconversation negotiator and involves notification and then the change ofstatus defined on the exchange conversation wrapper. An audit trial ismaintained of past exchange conversation accreditors within the exchangeconversation wrapper. If there was a prior agreement with the exchangeconversation accreditor to release their exchange conversation shares inthe case that they loose their exchange conversation accreditor statusthen the share allocation is removed. If there was no prior agreementthe current exchange conversation accreditor may agree to release theirshares in consultation with the exchange conversation asset negotiator.The shares withdrawn become part of the audit trail within the exchangeconversation asset wrapper. The exchange conversation accreditor maywish to retain all or part of their shares.

In one embodiment, the exchange conversation accreditor may not have theauthority to change a conversation asset or a conversation AI entityasset.

In one embodiment, the exchange conversation negotiator may removeshares 728, which belong to a member, which may be addressed by theexchange conversation negotiator and involves notification and then theremoval of exchange conversation asset shares, which requires an updateto the exchange conversation wrapper. An audit trial is maintained ofdeleted shares within the exchange conversation wrapper.

In one embodiment, the exchange conversation wrapper references theexchange conversation brand 729, which is a 1:1 relationship. In oneimplementation, the change to the exchange conversation asset brand isthe responsibility of the exchange conversation asset owner. An audittrial is maintained of changes to the exchange conversation asset brandwithin the exchange conversation wrapper.

In one embodiment, the exchange conversation wrapper references eachportfolio conversation asset and within this grouping every conversationasset 730, which is a 1:1:m relationship. The portfolio conversationasset and the associated conversation assets may be developed byexchange conversation members, and thus follows a similar manner asdiscussed for portfolio conversation assets. For conversation assetsdeveloped outside the domain of the exchange, the conversation assetauthor may wish to become a member of the exchange so that theirconversation assets can be reviewed and receive an accreditation rating.In one implementation, the exchange conversation owner through theirexchange conversation negotiator would point the conversation assetowner to one of their portfolio conversation assets and then similarmethods discussed for portfolio conversation assets may be applied.

In one embodiment, the exchange conversation wrapper references eachportfolio conversation asset and within this grouping every conversationAI entity asset 731, which is a 1:1:m relationship. The portfolioconversation asset and the associated conversation AI entity assets maybe developed by exchange conversation members, and then follow similarmanners discussed for portfolio conversation assets. For conversation AIentity assets developed outside the domain of the exchange, theconversation asset designer may wish to become a member of the exchangeso that their conversation AI entity assets can be reviewed and receivean accreditation rating. The exchange conversation owner through theirexchange conversation negotiator would point the conversation AI entityasset owner to one of their portfolio conversation assets and then themethods discussed for portfolio conversation assets may be applied.

In one embodiment, the exchange conversation wrapper references for eachexchange conversation member their bio 732, which is a 1:1 relationship.

In one embodiment, an exchange conversation wrapper maintains a counterof the dialogue-steps 733 within digital conversations, for eachconversation asset within each portfolio conversation asset.

In one embodiment, an exchange conversation wrapper maintains a counterof the conversation asset events 734 triggered by digital conversations,for each conversation asset within each portfolio conversation asset.

In one embodiment, an exchange conversation wrapper maintains a counterof the conversation asset widgets 735 triggered by digitalconversations, for each conversation asset within each portfolioconversation asset.

In one embodiment, an exchange conversation wrapper maintains a counterof the conversation asset display adverts 736 triggered by digitalconversations, for each conversation asset within each portfolioconversation asset.

In one embodiment, an exchange conversation wrapper maintains a counterof the conversation asset web-services 737 triggered by digitalconversations, for each conversation asset within each portfolioconversation asset.

In one embodiment, an exchange conversation wrapper maintains a counterof the conversation AI entity 3^(rd) party brands 738 triggered bydigital conversations, for each conversation AI entity asset within eachportfolio conversation asset.

In one embodiment, all interactions and transactions related to theexchange conversation asset are stored as an audit that provides a basisfor future projected value 739. The retrieved audit history includescategorization by the portfolio conversation assets, which is accessiblefrom the exchange conversation wrapper.

In one embodiment, an exchange conversation wrapper maintains a list ofexchange conversation members that also have the status of exchangeconversation authors 740, which are categorized by their respectiveportfolio conversation asset.

In one embodiment, an exchange conversation wrapper maintains a list ofexchange conversation members that also have the status of exchangeconversation designers 741, which are categorized by their respectiveportfolio conversation asset.

In one embodiment, the Exchange Conversation Wrapper may be used toestablish references to other exchange conversation assets 742, whichmay involve the trading of Exchange conversation asset shares or theassignment of exchange conversation asset shares new shares between therespective exchange conversation asset negotiators 745.

FIG. 8A provides a logic flow diagram illustrating pricing a virtualasset within embodiments of the DCM-Platform. In one embodiment, anasset owner, e.g., a conversation asset owner as discussed in FIGS.4B-4D, a conversation AI entity asset owner as discussed in FIGS. 5A-5C,a portfolio asset owner as discussed in FIGS. 6A-6C, an exchange assetowner as discussed in FIGS. 7A-7D, etc., may determine a dollar valuefor a dialogue step 805 in a conversation. In one implementation, theasset owner may determine the value based on past pricing information ofsimilar dialogue steps. For example, to price a dialogue line “I preferhair dresser for straight and sleek hair styles,” the asset owner mayconsider past pricing information indicative of consumer preferences onhair dressers.

In another implementation, the DCM-Platform may receive relatedtrading/pricing information 810 from a trading platform as a referenceof price determination. For example, pricing information of conversationassets from the same author may be grouped to provide relevant pricinginformation.

In one implementation, the value of a dialogue may be determined basedon the contents, e.g., whether there is an outcome 815, etc. Forexample, if a dialogue starts with a question from an AI entity “whatkind of hair dresser are you looking for?”, and an outcome is generatedfrom the consumer's dialogue response “I prefer hair dresser forstraight and sleek hair styles,” then such dialogue may be priced higherthan a dialogue without any outcome, e.g., the consumer's response doesnot address any preferences:“I don't know.” If no outcome is generated,the DCM-Platform may continue to price the next dialogue step.

In one implementation, if an outcome is included in a dialogue step, theDCM-Platform may search received trading information related to similaroutcomes 820, and based on the searched pricing information, theDCM-Platform may adjust the price of the dialogue step 826. For example,the trading information of conversations comprising outcomes indicatingconsumer's preferences of hair dressers may reflect the supply-demandrelationship of such information on the market, and if the demand ishigh, the DCM-Platform may price the dialogue step higher accordingly.

In one implementation, the DCM-Platform may continue to determine everydialogue step in a conversation, based on which the price of aconversation asset, a conversation AI entity asset 830, a portfolioasset and an exchange asset 835 may be determined. The DCM-Platform maythen update the wrapper of the virtual asset and submit pricinginformation for a transaction 840.

FIG. 8B provides a logic flow diagram illustrating asset monetizationwithin alternative embodiments of the DCM-Platform. In oneimplementation, the DCM-Platform may receive asset information of avirtual asset owner 845, such as, but not limited to asset ownershipinformation, asset authorship information, asset description, assettitle, asset icon information, and/or the like.

Within implementations, the DCM-Platform may facilitate the initiationof monetization by obtaining a corporate certificate of the asset owner,and/or credentials from an investor 850. The DCM-Platform may thenassign intellectual property rights associated with the digital assetsto the investor 855, and then determine shares of stock and price of astock share 865 based on the pricing information submitted by the assetowner.

In one implementation, the DCM-Platform may determine cost factorsassociated with the monetization 870, such as, but not limited tooperational cost, advertisement cost, and/or the like. The DCM-Platformmay then determine a dividends payment structure based on the determinedstock shares and the cost factors 875, and facilitate transfer of stockshares 880. For example, the DCM-Platform may generate a financialinstrument based on the stock shares, such as futures, forwards, optionsand/or the like, which are based on the underlying virtual assets, andsubmit to a financial trading platform for transactions.

Alternative Embodiments of DCM-Platform Asset Pricing

In one embodiment, the method for the determination of a ConversationAsset Index is influenced by whether it is standalone or part of aPortfolio Conversation or an Exchange Conversation. This method appliesto the standalone Conversation Asset. In one implementation, the methodinvolves two parts: Interaction (Conversation Asset Interaction Index)and Monetary (Conversation Asset Monetary Index)

In one embodiment, every digital conversation interaction involves oneor more conversation-steps. A conversation-step contains the followingattributes: the dialogue, the date and time the conversation-stepstarted, the number of words within the dialogue, the number ofdialogue-options, which can be zero or more, the selectedcountry/language.

In one embodiment, each conversation-step interaction is recorded andstored in an archive with the dialogue together with the attributesabove.

In one embodiment, the conversation asset interaction index is updatedfor each conversation-step as follows: go back to the previousconversation-step, which is not relevant for the firstconversation-step; go to the next conversation-step which is relevantwhen there are no dialogue-options present but is not relevant in thecase of the last conversation-step; selected a dialogue-option and movesto the next contextual conversation-step with interaction counter pointfor each appropriate backward forward or selected option taken.

In one embodiment, each Digital Conversation has a start and an endpoint. This is known as a Conversation-String. There is a minimum of oneConversation-Step for each Conversation-String, but there is no limit tothe number of Conversation-Steps within a Conversation-String.Therefore, every action taken whether it is Forward, Backward orSelected adds another node to the Conversation-String. TheConversation-String can be extended across multiple user sessions andtherefore is not constrained by time. The Conversation Asset InteractionIndex is the aggregation of points derived from theConversation-Strings. Stored with the Conversation-String is theattributes defined above so this enables the calculation of the time ittook to undertake a Digital Conversation though this does not impact theConversation Asset Interaction Index.

In one embodiment, there is a Conversation-Link betweenConversation-Assets then the Conversation-String continues unabated byaccumulating the Interaction Counter Points. There is no constraint inthe use of Conversation-Links between Conversation-Assets. Therefore, aConversation-String may encompass any number of Conversation-Assets.There is no limit to the number of Conversation-Steps that can becounted and update the Conversation Asset Interaction Index. The firstConversation-Asset is the origination of the Conversation-String andtherefore has its own Conversation Asset Interaction Index. However,each Conversation Asset has its own Conversation-String and its ownConversation Asset Interaction Index, which are also updated even thoughthey may not be the origination for a given Digital Conversation.Example: Let's take three Conversation Assets called CA1, CA2 and CA3.The interaction starts with CA1 and involves 3 Conversation-Steps. TheCA1 Index is set to 3 Interaction Points. The CA1 Conversation Link goesto CA2 that involves 4 Conversation-Steps. The CA1 Index is now set to 7Interaction Points and the CA2 Index is now set to 4 Interaction Points.The CA2 Conversation Link goes to CA3 that involves 5Conversation-Steps. The CA1 Index is now set to 12 Interaction Points,the CA2 Index is now set to 9 Interaction Points and the CA3 Index isnow set to 5 Interaction Points.

In one embodiment, there are no deductions to the Conversation AssetInteraction Index for standalone Conversation Assets.

In one embodiment, the Conversation Asset Interaction Index consistentlyis applied across changed versions of the Conversation Asset. However, ahistorical audit is kept by Conversation Asset versions for trend andcomparison analysis. This means the Conversation Asset Interaction Indexprovides a life time view of the Conversation Asset's interactionperformance.

In one embodiment, the Conversation Asset Interaction Index and theassociated attributes of the Digital Conversation usage as describedabove are maintained with the Conversation Asset Wrapper.

In one embodiment, the Conversation Asset Monetary Index is theaccumulative numeric value associated with the Conversation Asset and ispegged to a global currency that is determined for the tradingassociated with the Conversation Asset.

In one embodiment, there are varies ways that a standalone ConversationAsset can be monetized to update the Conversation Asset Monetary Index,as follows:

The DCM-Platform may sell conversation asset shares;

For example, in one embodiment, where monetary value has been exchangedfor Conversation Assets Shares this is logged to the Conversation AssetMonetary Index. So say one sold 10 shares out of 100 shares for aConversation Asset for say $20 each. Once the transaction has beenlogged within the Conversation Asset Wrapper then the Conversation Assetis now worth in total 2,000 Monetary Points (100 shares*$20) plus anyadditional monetary value sourced from elsewhere—see below. If one moreConversation Asset share is sold for $10 then the Conversation Asset isnow worth in total 1,000 Monetary Points (100 shares*$10) plus anyadditional monetary value sourced from elsewhere. But if the next issold for $30 then the Conversation Asset is now worth in total 3,000Monetary Points (100 shares*$30) plus any additional monetary valuesourced from elsewhere—see below. If no Conversation Assets Shares aresold then the Conversation Asset Monetary Index cannot be altered forthis consideration (100 shares*$0).

In one embodiment, the DCM-Platform may swap conversation asset shares;

In one embodiment, this is treated in the same way as for SellConversation Asset Shares. The difference is that if a swap is withanother Conversation Asset Shares and if this Conversation Asset Sharehas a monetary value then the current value is used as the bid price andis then treated like money. So if the Conversation Asset is worth $100per share and it swaps 1 share for 2 shares then the bid price equatesto $50 a share (100 shares*$50) thus the Conversation Asset is now worthin total 5,000 Monetary Points plus any additional monetary valuesourced from elsewhere.

Swap Conversation AI Entity Asset Shares

In one embodiment, this is treated in the same way as for SellConversation Asset Shares. The difference is that if a swap is with aConversation AI Entity Asset Shares and if this Conversation AI EntityAsset Share has a monetary value then the current value is used as thebid price and is then treated like money. So if the Conversation AIEntity Asset is worth $100 per share and it swaps 1 share for 2 sharesthen the bid price equates to $50 a share (100 shares*$50) thus theConversation Asset is now worth in total 5,000 Monetary Points plus anyadditional monetary value sourced from elsewhere—see below.

Conversation Display Advertising

In one embodiment, if monetary value is received for contextConversation Display Advertising or marketing then the transaction islogged in the Conversation Asset Wrapper and the Conversation AssetMonetary Index is updated accordingly. The term period for this monetaryvalue is defaulted to one year unless a specific contract has beennegotiated. Once this transaction has been updated into the ConversationAsset the Conversation Asset Monetary Index is updated for the period ofthe monetary term. For example: if the advert is a dollar per displaythen the Conversation Asset Monetary Index is updated by one monetarypoint that is removed after 1 year. If however, it was negotiated thatan advert would be permanently displayed at a given Conversation-Stepfor $1,000 for 3 months then the Conversation Asset Monetary Index isupdated by 1,000 Monetary Points but the amount is removed from theConversation Asset Monetary Index at the end of the 3 month period.

In one embodiment, the Conversation Asset Monetary Index is only updatedfor the specific Conversation Asset and not for that Conversation Assetthat it directly or indirectly has Conversation Links. However, if theConversation Asset Negotiator of a direct or indirect LinkedConversation Asset agrees to a pro rata monetary value for triggeredConversation Display Advert due to an earlier Digital Conversation butwithin the same Conversation-String then this pro rata value is added tothe Conversation Asset Monetary Index.

In one embodiment, it should be remembered that Conversation DisplayAdverts can be triggered for each specific Conversation-Step.

3^(rd) Party Conversation Events

In one embodiment, if monetary value is received for triggering a 3^(rd)Party Conversation Event then the transaction is logged in theConversation Asset Wrapper and the Conversation Asset Monetary Index isupdated accordingly.

In one embodiment, the conditions and the term period for eachConversation Event are specifically negotiated.

In one embodiment, the negotiation could be a fixed price for a giventerm period regardless to the number of times a Conversation Event istriggered. In this case, once this transaction has been updated into theConversation Asset the Conversation Asset Monetary Index is updated forthe period of the monetary term but removed from the Conversation AssetMonetary Index at the end of the negotiated term period.

In one embodiment, the negotiation could be a fee-based price for eachtime a specific Conversation Event is triggered. For example: If theConversation Event is a dollar per Conversation Event triggered then theConversation Asset Monetary Index is immediately updated by the agreedmonetary unit whenever this trigger occurs. These Monetary Points areremoved after the agreed term period negotiated.

In one embodiment, the negotiation may be time sensitive so events aretriggered only within an agreed time period. This may involve a fixedand/or variable set of conditions including a cap to limit liability.Alternatively, different Conversation Events can be triggered bydifferent Dialogue-Options. Regardless of these variations the methodstill applies that the Conversation Asset Monetary Index is updatedaccordingly whether to add or delete monetary points.

In one embodiment, the Conversation Asset Monetary Index is only updatedfor the specific Conversation Asset and not for that Conversation Assetthat it directly or indirectly has Conversation Links. However, if theConversation Asset Negotiator of a direct or indirect LinkedConversation Asset agrees to a pro rata monetary value for triggeredConversation Events due to an earlier Digital Conversation but withinthe same Conversation-String then this pro rata value is added to theConversation Asset Monetary Index.

In one embodiment, it should be remembered that Conversation Event canbe triggered for each specific Conversation-Step.

3^(rd) Party Conversation Widgets

In one embodiment, if monetary value is received for triggering a 3^(rd)Party Conversation Widget then the transaction is logged in theConversation Asset Wrapper and the Conversation Asset Monetary Index isupdated accordingly.

In one embodiment, the conditions and the term period for eachConversation Widget are specifically negotiated.

In one embodiment, the negotiation could be a fixed price for a giventerm period regardless to the number of times a Conversation Widget istriggered. In this case, once this transaction has been updated into theConversation Asset the Conversation Asset Monetary Index is updated forthe period of the monetary term but removed from the Conversation AssetMonetary Index at the end of the negotiated term period.

In one embodiment, the negotiation could be a fee-based price for eachtime a specific Conversation Widget is triggered. For example: If theConversation Widget is a dollar per Conversation Widget triggered thenthe Conversation Asset Monetary Index is immediately updated by theagreed monetary unit whenever this trigger occurs. These Monetary Pointsare removed after the agreed term period negotiated.

In one embodiment, the negotiation could be a commission-based price foreach time a specific Conversation Widget that results with an agreeoutcome such as the purchase of a product or the provision ofpersonalized information. For example: If the Conversation Widget is 10%of a product purchase then this monetary value is added to theConversation Asset Monetary Index. These Monetary Points are removedafter the agreed term period negotiated.

In one embodiment, the negotiation may be time sensitive so events aretriggered only within an agreed time period. This may involve a fixedand/or variable set of conditions including a cap to limit liability.Alternatively, different Conversation Widget can be triggered bydifferent Dialogue-Options. Regardless of these variations the methodstill applies that the Conversation Asset Monetary Index is updatedaccordingly whether to add or delete monetary points.

In one embodiment, the Conversation Asset Monetary Index is only updatedfor the specific Conversation Asset and not for that Conversation Assetthat it directly or indirectly has Conversation Links. However, if theConversation Asset Negotiator of a direct or indirect LinkedConversation Asset agrees to a pro rata monetary value for triggered aConversation Widget due to an earlier Digital Conversation but withinthe same Conversation-String then this pro rata value is added to theConversation Asset Monetary Index.

In one embodiment, it should be remembered that Conversation Widget canbe triggered for each specific Conversation-Step.

Handoffs

In one embodiment, the Conversation Asset Monetary Index is only updatedfor the specific Conversation Asset and not for other ConversationAssets that are linked to; so a Conversation Asset through DigitalConversation could handoff to another Conversation Asset.

In one embodiment, however, if the Conversation Asset Negotiator of adirect or indirect Linked Conversation Asset agrees to a pro ratamonetary value for a handoff then this pro rata value is added to theConversation Asset Monetary Index with the inherited terms.

Subscription-Based Digital Conversations

In one embodiment, if monetary value is received for subscription-basedDigital Conversations then the transaction or pro-rated part of thetransaction is logged in the Conversation Asset Wrapper and theConversation Asset Monetary Index is updated accordingly. The termperiod for this monetary value is defaulted to one year unless aspecific contract has been negotiated. Once this transaction has beenupdated into the Conversation Asset the Conversation Asset MonetaryIndex is updated for the period of the monetary term. For example: ifthe subscription is an annualized $1,000 to access ten ConversationAssets then the Conversation Asset Monetary Index could be updated by100 Monetary Points if prorated on an equal spread, but the amount isremoved from the Conversation Asset Monetary Index at the end of the 12month period. Alternative disbursement means can be used.

Conversation-Steps Meter

In one embodiment, the Conversation-Steps can be metered for DigitalConversation interactions and the associated transaction is logged inthe Conversation Asset Wrapper and the Conversation Asset Monetary Indexis updated accordingly. The term period for this monetary value isdefaulted to one year unless a specific alternative period isdetermined. Once this transaction has been updated into the ConversationAsset the Conversation Asset Monetary Index is updated for the period ofthe monetary term. For example: if the meter is $10 perConversation-Step and the interaction involved 20 Conversation-Stepsthen the transaction is valued at $200 then the Conversation AssetMonetary Index would be updated by 100 Monetary Points, but the amountis removed from the Conversation Asset Monetary Index at the end of a 12month period.

Conversation-Outcome Metered

In one embodiment, the Conversation-Outcomes can be metered for DigitalConversation interactions and the associated transaction is logged inthe Conversation Asset Wrapper and the Conversation Asset Monetary Indexis updated accordingly. The term period for this monetary value isdefaulted to one year unless a specific alternative period isdetermined. Once this transaction has been updated into the ConversationAsset the Conversation Asset Monetary Index is updated for the period ofthe monetary term. For example: if the meter is $40 for a specificConversation-Outcome and $20 for a different Conversation-Outcome thenthe Conversation Asset Monetary Index would be updated by 40 and 20Monetary Points respectively, but the amount is removed from theConversation Asset Monetary Index at the end of a 12 month period.

Digital Conversation Auction

In one embodiment, the Digital Conversation can be auctioned thusintroducing scarcity into the supply/demand equation. The auctiontransaction is logged in the Conversation Asset Wrapper and theConversation Asset Monetary Index is updated accordingly. The termperiod for this monetary value is defaulted to one year unless aspecific alternative period is determined. Once this transaction hasbeen updated into the Conversation Asset the Conversation Asset MonetaryIndex is updated for the period of the monetary term. For example: ifthe auction paid $10,000 for a specific Digital Conversation then theConversation Asset Monetary Index would be updated by 10,000 MonetaryPoints respectively, but the amount is removed from the ConversationAsset Monetary Index at the end of a 12 month period.

Conversational Intelligence

In one embodiment, the Digital Conversation Audit providesConversational Intelligence that can be copied and sold, or accessed oraggregated with 3^(rd) party data, as a one off or for an agreed periodin exchange for a monetary value. The Conversational Intelligencetransaction or prorated if shared with others is logged in theConversation Asset Wrapper and the Conversation Asset Monetary Index isupdated accordingly. The term period for this monetary value isdefaulted to one year unless a specific alternative period isdetermined. Once this transaction has been updated into the ConversationAsset the Conversation Asset Monetary Index is updated for the period ofthe monetary term. For example: if a copy of 3 months DigitalConversation is sold for $500 then the Conversation Asset Monetary Indexwould be updated by 500 Monetary Points respectively, but the amount isremoved from the Conversation Asset Monetary Index at the end of a 3month period.

Other Monetary Options

In one embodiment, the methods above show a diverse range of methods formonetization of a Conversation Asset. This does not negate other methodsof monetization but the underlying method for the assignment of MonetaryPoints still stands.

Example Conversation Asset Index

In one embodiment, the Conversation Asset Index is formula driven and iscalculated by Conversation Asset Interaction Index+Conversation AssetMonetary Index.

In one embodiment, every change to the Conversation Asset Index islogged with a date and time stamp for trend analysis and future valuepredictions and trading.

In one embodiment, the Conversation Asset Index, Conversation AssetInteraction Index and the Conversation Asset Monetary Index values arecaptured on a daily, weekly, monthly and annual basis for trend analysisand future value predictions and trading.

In one embodiment, all the above information is accessible via theConversation Asset Wrapper defined by the Conversation Asset GlobalIdentity.

In one embodiment, further breakdowns of the Indexes can be viewed by:versions of the conversation asset; conversation link(s), conversationevent(s), conversation widget(s), conversation advert(s).

In one embodiment, the Index is not calculated when the ConversationAsset Status is anything but ‘Production’.

Example Aggregation of the Conversation Asset Index

In one embodiment, the Conversation Asset Index, Conversation AssetInteraction Index and the Conversation Asset Monetary Index values arealso stored individually and at an aggregated level across all relatedConversation Assets for the following: conversation asset ownership,conversation asset negotiator, conversation asset primary script author,conversation asset other script author(s), conversation AI entity asset.

Example Method for Determining a Standalone Conversation Ai EntityPerformance Index

In one embodiment, the method for the determination of a Conversation AIEntity Performance Index is influenced by whether it is standalone orpart of a Portfolio Conversation or an Exchange Conversation. Thismethod applies only to the standalone Conversation AI Entity Asset. TheConversation AI Entity Performance Index is an associated method anddoes not reflect the actual monetization as an earning asset for theConversation AI Entity Asset as this is addressed in the next chapter.

Example Conversation AI Entity Performance Index Method Involves TwoParts

Interaction (Conversation AI Entity Interaction Performance Index)

Monetary (Conversation AI Entity Monetary Performance Index)

Example Interaction

In one embodiment, as already described the associated ConversationAsset Interaction Index is also stored against the Conversation AIEntity Asset and therefore becomes the Conversation AI EntityInteraction Performance Index.

In one embodiment, as a Conversation AI Entity Asset can be involvedwith more than one primary Conversation Assets then the Conversation AIEntity Interaction Performance Index is the aggregation of theassociated Conversation Asset Interaction Indexes.

In one embodiment, the Conversation AI Entity Interaction PerformanceIndex consistently is applied across changed versions of theConversation AI Entity. However, a historical audit is kept byConversation AI Entity versions for trend and comparison analysis. Thismeans the Conversation AI Entity Interaction Performance Index providesa life time view of the Conversation AI Entity's interactionperformance.

In one embodiment, the Conversation AI Entity Interaction PerformanceIndex and the associated attributes of the interactions are maintainedwith the Conversation AI Entity Wrapper.

In one embodiment, as already described the associated ConversationAsset Monetary Index is also stored against the associated ConversationAI Entity Asset and therefore becomes the Conversation AI EntityMonetary Performance Index.

In one embodiment, as a Conversation AI Entity Asset can be involvedwith more than one primary Conversation Assets then the Conversation AIEntity Monetary Performance Index is the aggregation of the associatedConversation Asset Monetary Indexes.

In one embodiment, the Conversation AI Entity Monetary Performance Indexis consistently applied across changed versions of the Conversation AIEntity. However, a historical audit is kept by Conversation AI Entityversions for trend and comparison analysis. This means the ConversationAI Entity Monetary Performance Index provides a life time view of theConversation AI Entity's monetary performance.

In one embodiment, the Conversation AI Entity Monetary Performance Indexand the associated attributes of the monetary transactions aremaintained with the Conversation AI Entity Wrapper.

Example Conversation AI Entity Performance Index

In one embodiment, the Conversation AI Entity Performance Index isformula driven and is calculated by Conversation AI Entity InteractionPerformance Index+Conversation AI Entity Monetary Performance Index.

In one embodiment, every change to the Conversation AI EntityPerformance Index is logged with a date and time stamp for trendanalysis and future value predictions and trading.

In one embodiment, the Conversation AI Entity Performance Index,Conversation AI Entity Interaction Performance Index and theConversation AI Entity Monetary Performance Index values are captured ona daily, weekly, monthly and annual basis for trend analysis and futurevalue predictions and trading.

In one embodiment, all the above information is accessible via theConversation AI Entity Asset Wrapper defined by the Conversation AIEntity Asset Global Identity.

In one embodiment, further breakdowns of the Indexes can be viewed by:versions of the conversation asset conversation link(s) conversationevent(s) conversation widget(s) conversation advert(s).

In one embodiment, the Index is not calculated when the Conversation AIEntity Asset Status is anything but ‘Production’.

Example Aggregation of the Conversation Asset Index

In one embodiment, the Conversation AI Entity Performance Index,Conversation AI Entity Interaction Performance Index and theConversation AI Entity Monetary Performance Index values are also storedindividually and at an aggregated level across all related conversationAI entity assets for the following: conversation AI entity assetownership conversation AI entity asset negotiator conversation AI entityasset primary designer conversation AI entity asset other designers(s).

Example Method for Determining a Standalone Conversation AI EntityMonetary Index

In one embodiment, the method for the determination of a Conversation AIEntity Monetary Index is influenced by whether it is standalone or partof a Portfolio Conversation or an Exchange Conversation. This methodapplies only to the standalone Conversation AI Entity Asset. TheConversation AI Entity Monetary Index is the monetization of aConversation AI Entity Asset as an earning asset.

In one embodiment, a Conversation AI Entity Monetary Index is theaccumulative numeric value associated with the Conversation AI EntityAsset and is pegged to a global currency that is determined for thetrading associated with the Conversation AI Entity Asset.

In one embodiment, there are varies ways that a standalone ConversationAI Entity Asset can be monetized to update the a Conversation AI EntityMonetary Index, as follows:

Sell Conversation AI Entity Asset Shares

In one embodiment, where monetary value has been exchanged forConversation AI Entity Assets Shares this is logged to the ConversationAI Entity Monetary Index. Look at similar contextual example above thatinvolved applying Monetary Points to the Conversation Asset MonetaryIndex.

Swap with Conversation Asset Shares

In one embodiment, this is treated in the same way as for SellConversation AI Entity Asset Shares. The difference is that if a swap iswith Conversation Asset Shares and if this Conversation Asset Share hasa monetary value then the current value is used as the bid price and isthen treated like money. Look at similar contextual example above thatinvolved applying Monetary Points to the Conversation Asset MonetaryIndex.

Swap with Other Conversation AI Entity Asset Shares

In one embodiment, this is treated in the same way as for SellConversation AI Entity Asset Shares. The difference is that if a swap iswith a Conversation AI Entity Asset Shares and if this Conversation AIEntity Asset Share has a monetary value then the current value is usedas the bid price and is then treated like money. Look at similarcontextual example above that involved applying Monetary Points to theConversation Asset Monetary Index.

AI Entity Brand Display

In one embodiment, if monetary value is received for context an AIEntity Brand Display (3^(rd) party brand being displayed as part of theAvatar inventory) then the transaction is logged in the Conversation AIEntity Asset Wrapper and Conversation AI Entity Monetary Index isupdated accordingly. The term period for this monetary value isdefaulted to one year unless a specific contract has been negotiated.Once this transaction has been updated into the Conversation AI EntityAsset the Conversation AI Entity Monetary Index is updated for theperiod of the monetary term. Look at similar contextual example abovethat involved applying Monetary Points to the Conversation AssetMonetary Index.

3^(rd) Party Conversation Events

In one embodiment, if monetary value is received for triggering a 3^(rd)Party Conversation Event then the transaction is logged in theConversation AI Entity Asset Wrapper and the Conversation Asset MonetaryIndex is updated accordingly.

In one embodiment, the conditions and the term period for eachConversation Event are specifically negotiated.

In one embodiment, the negotiation could be a fixed price for a giventerm period regardless to the number of times a Conversation Event istriggered. In this case, once this transaction has been updated into theConversation AI Entity Asset the Conversation AI Entity Monetary Indexis updated for the period of the monetary term but removed from theConversation AI Entity Monetary Index at the end of the negotiated termperiod.

In one embodiment, the negotiation could be a fee-based price for eachtime a specific Conversation Event is triggered. For example: If theConversation Event is a dollar per Conversation Event triggered then theConversation AI Entity Monetary Index is immediately updated by theagreed monetary unit whenever this trigger occurs. These Monetary Pointsare removed after the agreed term period negotiated.

In one embodiment, the negotiation may be time sensitive so events aretriggered only within an agreed time period. This may involve a fixedand/or variable set of conditions including a cap to limit liability.Alternatively, different Conversation Events can be triggered bydifferent Dialogue-Options. Regardless of these variations the methodstill applies that the Conversation AI Entity Monetary Index is updatedaccordingly whether to add or delete monetary points.

3^(rd) Party Conversation Widgets

In one embodiment, if monetary value is received for triggering a 3^(rd)Party Conversation Widget then the transaction is logged in theConversation AI Entity Asset Wrapper and the Conversation AI EntityMonetary Index is updated accordingly.

In one embodiment, the conditions and the term period for eachConversation Widget are specifically negotiated.

In one embodiment, the negotiation could be a fixed price for a giventerm period regardless to the number of times a Conversation Widget istriggered. In this case, once this transaction has been updated into theConversation AI Entity Asset the Conversation AI Entity Monetary Indexis updated for the period of the monetary term but removed from theConversation AI Entity Monetary Index at the end of the negotiated termperiod.

In one embodiment, the negotiation could be a fee-based price for eachtime a specific Conversation Widget is triggered. For example: If theConversation Widget is a dollar per Conversation Widget triggered thenthe Conversation AI Entity Monetary Index is immediately updated by theagreed monetary unit whenever this trigger occurs. These Monetary Pointsare removed after the agreed term period negotiated.

In one embodiment, the negotiation could be a commission-based price foreach time a specific Conversation Widget that results with an agreeoutcome such as the purchase of a product or the provision ofpersonalized information. For example: If the Conversation Widget is 10%of a product purchase then this monetary value is added to theConversation AI Entity Monetary Index. These Monetary Points are removedafter the agreed term period negotiated.

In one embodiment, the negotiation may be time sensitive so events aretriggered only within an agreed time period. This may involve a fixedand/or variable set of conditions including a cap to limit liability.Alternatively, different Conversation Widgets can be triggered bydifferent Dialogue-Options. Regardless of these variations the methodstill applies that the Conversation AI Entity Monetary Index is updatedaccordingly whether to add or delete monetary points.

Handoffs

In one embodiment, the Conversation AI Entity Monetary Index is onlyupdated for the specific Conversation AI Entity Asset and not forConversation AI Entity Assets that are linked to; so an AI Entitythrough Digital Conversation or through a display within its landscapecould handoff to another Conversation AI Entity.

In one embodiment, however, if the Conversation AI Entity AssetNegotiator of a direct or indirect linked Conversation AI Entity Assetagrees to a pro rata monetary value for a handoff then this pro ratavalue is added to the Conversation AI Entity Monetary Index with theinherited terms.

Subscription-Based Digital Conversations

In one embodiment, if monetary value is received for subscription-basedDigital Conversations then the transaction or pro-rated part of thetransaction can be assigned to the Conversation AI Entity. In this caseit is logged in the Conversation AI Entity Asset Wrapper and theConversation AI Entity Monetary Index is updated accordingly subject tothe terms. Look at similar contextual example above that involvedapplying Monetary Points to the Conversation Asset Monetary Index.

Conversation-Steps Meter

In one embodiment, the Conversation-Steps can be metered for DigitalConversation interactions and the associated transaction or pro-ratedpart of the transaction can be assigned to the Conversation AI Entity.In this case it is logged in the Conversation AI Entity Asset Wrapperand the Conversation AI Entity Monetary Index is updated accordinglysubject to the terms. Look at similar contextual example above thatinvolved applying Monetary Points to the Conversation Asset MonetaryIndex.

Conversation-Outcome Metered

In one embodiment, the Conversation-Outcomes can be metered for DigitalConversation interactions and the associated transaction or pro-ratedpart of the transaction can be assigned to the Conversation AI Entity.In this case it is logged in the Conversation AI Entity Asset Wrapperand the Conversation AI Entity Monetary Index is updated accordinglysubject to the terms. Look at similar contextual example above thatinvolved applying Monetary Points to the Conversation Asset MonetaryIndex.

Conversation AI Entity Auction

In one embodiment, the Conversation AI Entity can be auctioned thusintroducing scarcity into the supply/demand equation. The auctiontransaction or pro-rated part of the transaction can be assigned to theConversation AI Entity. In this case it is logged in the Conversation AIEntity Asset Wrapper and the Conversation AI Entity Monetary Index isupdated accordingly subject to the terms. Look at similar contextualexample above that involved applying Monetary Points to the ConversationAsset Monetary Index.

Conversational Intelligence

In one embodiment, the Digital Conversation Audit providesConversational Intelligence that can be copied and sold, or accessed oraggregated with 3^(rd) party data, as a one off or for an agreed periodin exchange for a monetary value. The Conversational Intelligencetransaction or pro-rated part of the transaction can be assigned to theConversation AI Entity. In this case it is logged in the Conversation AIEntity Asset Wrapper and the Conversation AI Entity Monetary Index isupdated accordingly subject to the terms. Look at similar contextualexample above that involved applying Monetary Points to the ConversationAsset Monetary Index.

Other Monetary Options

In one embodiment, the methods above show a diverse range of methods formonetization of a Conversation AI Entity Asset. This does not negateother methods of monetization but the underlying method for theassignment of Monetary Points still stands.

Example Method for Determining a Portfolio Conversation Asset Index

In one embodiment, the method for the determination of a PortfolioConversation Asset Index is the aggregation and portfolio-basedweightings for:

Portfolio Conversation Asset Index=Sum of the Conversation Asset Indexesthat have been branded by the Portfolio and are within the rules ofengagement defined earlier.

Portfolio Conversation Asset Interaction Index=Sum of the ConversationAsset Interaction Indexes that have been branded by the Portfolio andare within the rules of engagement defined earlier.

Portfolio Conversation Asset Monetary Index=Sum of the ConversationAsset Monetary Indexes that have been branded by the Portfolio and arewithin the rules of engagement defined earlier.

Portfolio Conversation AI Entity Performance Index=Sum of theConversation AI Entity Performance Indexes that have been branded by thePortfolio and are within the rules of engagement defined earlier.

Portfolio Conversation AI Entity Interaction Performance Index=Sum ofthe Conversation Interaction AI Entity Performance Indexes that havebeen branded by the Portfolio and are within the rules of engagementdefined earlier.

Portfolio Conversation AI Entity Monetary Performance Index=Sum of theConversation AI Entity Monetary Performance Indexes that have beenbranded by the Portfolio and are within the rules of engagement definedearlier.

Portfolio Conversation AI Entity Monetary Index=Portfolio ConversationAI Entity Monetary Index+Sum of the Portfolio Conversation AI EntityMonetary Indexes that have been branded by the Portfolio and are withinthe rules of engagement defined earlier.

The Portfolio Conversation Asset contains all the permutationsassociated with Conversation Assets and Conversation AI Entity Assetscovered earlier.

Example Portfolio Conversation Tariffs

In one embodiment, the Portfolio Conversation Asset governs the monetaryrules of engagement that apply to all the associated Conversation Assetsand the AI Entity Assets that have been covered earlier for theindividual asset classes.

Example Portfolio Interaction Weightings

In one embodiment, the Portfolio Conversation Asset governs theweighting rules of engagement that apply to all the associatedConversation Assets and the AI Entity Assets that have been coveredearlier for the individual asset classes. These weighting rules can begoverned by the Portfolio and can be established for any permutation ofinfluence including:

Portfolio Conversation Asset Feedback for example, if the Portfolio hasa weighting value of 5 for five star feedback then the number ofConversation-Steps can be multiplied by a number assigned by thePortfolio; thus 20 Conversation-Steps is multiplied by 2 for a five starfeedback equating to 40 weighted Conversation-Steps that are applied tothe Interaction Index.

Portfolio Conversation Asset Review for example, if the Portfolio has aweighting value of 3 for a top review of a Conversation Asset then thenumber of Conversation-Steps can be multiplied by a number assigned bythe Portfolio; thus 20 Conversation-Steps is multiplied by 3 for a topreview feedback equating to 60 weighted Conversation-Steps that areapplied to the Interaction Index.

Portfolio Conversation Asset Outcomes for example, if the Portfolio hasassigned a weighting value of 10 for a primary Conversation Outcome thenthe number of Conversation-Steps can be multiplied by a 10 equating to1000 weighted Conversation-Steps that are applied to the InteractionIndex.

Further weightings applied in a similar way to the above can be given tothe following and again can be varied according to associated variables:portfolio conversation display advert portfolio conversation widgetportfolio conversation event. A Portfolio Conversation Asset can combineother variables such as country and any permutation of the above toapply weightings to the Portfolio Interactions.

The approach to these weighting for Conversation Asset Interactions alsoapplied to the Conversation AI Entity Interactions, which can be treatedthe same or at a Portfolio chosen variant.

The Portfolio Weightings are not applied to the monetary indexes as issimply a monetary actualization.

Example Portfolio Conversation Liquidity Index

In one embodiment, the Portfolio Conversation Liquidity Index monitorsthe trends for the accumulative monetary movements covering: portfolioconversation asset monetary index portfolio conversation AI entitymonetary index.

In one embodiment, as the Portfolio Conversation Liquidity Index isupdated as monetary changes occur the Portfolio Conversation LiquidityIndex can show trends by: hour, day, month, year.

In one embodiment, these trends can be drilled down into the PortfolioConversation Asset Monetary Index and the Portfolio Conversation AIEntity Monetary Index. In turn these Indexes can be drill down into theactual transactions detailed earlier.

In one embodiment, should the Portfolio Conversation Liquidity Index bezero or indeed stagnates (no changes over time) then this means thePortfolio is illiquid.

Example Portfolio Conversation Capital Index

In one embodiment, the Portfolio Conversation Capital Index monitors thetrends for the accumulative asset share price movements covering:Portfolio Conversation Assets, Portfolio Conversation AI Entity Assets.

In one embodiment, the Portfolio Conversation Capital Index changeswhenever Conversation Assets are added or removed to the productionportfolio and an Asset Share Price has been applied or Conversation AIEntity Assets are added or removed to the production portfolio and anAsset Share Price has been applied or Asset Share has been traded.

In one embodiment, the latest Asset Share Price used for a transactionis applied to all the Shares of the Asset: Total Asset Shares*LatestCurrent Share Price; the currency used is determined by the PortfolioOwner.

In one embodiment, the Portfolio Conversation Capital Index is theaccumulative calculated share value for all the Assets within thePortfolio.

In one embodiment, the Portfolio Conversation Capital Index can showtrends by: hour, day, month, year.

In one embodiment, these trends can be drilled down into the Asset Sharetransactions.

In one embodiment, should the Portfolio Conversation Capital Index bezero then this means the Portfolio has not been capitalized.

Example Portfolio Conversation Future Index

In one embodiment, the Portfolio Conversation Future Index is the futuretrend for the accumulation of the following: Portfolio ConversationLiquidity Index, Portfolio Conversation Capital Index, The PortfolioFuture=Portfolio Conversation Liquidity Index+Portfolio ConversationCapital Index and is calculated forward based on past trends coveringweekly, monthly and yearly projections. The Portfolio ConversationFuture Index can be adjusted by weightings over time set by thePortfolio. The primary purpose of the Portfolio Conversation FutureIndex is for Asset Share Investors and derivative trades. Forwardprojections may also be calculated with Portfolio based adjustments for:Portfolio Conversation Asset Index, Portfolio Conversation AssetInteraction Index, Portfolio Conversation Asset Monetary Index,Portfolio Conversation AI Entity Performance Index, PortfolioConversation AI Entity Interaction Performance Index, PortfolioConversation AI Entity Monetary Performance Index, PortfolioConversation AI Entity Monetary Index

In one embodiment, should the Portfolio Conversation Future Index bezero then this means the Portfolio is illiquid.

Example Method for Determining a Exchange Conversation Asset Index

In one embodiment, the method for the determination of an ExchangePortfolio Conversation Asset Index is the aggregation andportfolio-based weightings for:

Exchange Conversation Asset Index = Sum of the Portfolio ConversationAsset Indexes that have been branded by the Exchange and are within therules of engagement defined earlier. Exchange Conversation AssetInteraction Index = Sum of the Portfolio Conversation Asset InteractionIndexes that have been branded by the Exchange and are within the rulesof engagement defined earlier. Exchange Conversation Asset MonetaryIndex = Sum of the Portfolio Conversation Asset Monetary Indexes thathave been branded by the Exchange and are within the rules of engagementdefined earlier. Exchange Conversation AI Entity Performance Index = Sumof the Portfolio Conversation AI Entity Performance Indexes that havebeen branded by the Exchange and are within the rules of engagementdefined earlier. Exchange Conversation AI Entity Interaction PerformanceIndex = Sum of the Portfolio Conversation Interaction AI EntityPerformance Indexes that have been branded by the Exchange and arewithin the rules of engagement defined earlier. Exchange Conversation AIEntity Monetary Performance Index = Sum of the Portfolio Conversation AIEntity Monetary Performance Indexes that have been branded by theExchange and are within the rules of engagement defined earlier.Exchange Conversation AI Entity Monetary Index = Exchange ConversationAI Entity Monetary Index + Sum of the Exchange Conversation AI EntityMonetary Indexes that have been branded by the Exchange and are withinthe rules of engagement defined earlier.

The Exchange Conversation Asset contains all the permutations associatedwith Conversation Assets and Conversation AI Entity Assets coveredearlier.

Example Exchange Conversation Tariffs

In one embodiment, the Exchange Conversation Asset governs the monetaryrules of engagement that apply to all the associated PortfolioConversation Assets and the Portfolio AI Entity Assets that have beencovered earlier for the individual asset classes.

Example Exchange Interaction Weightings

In one embodiment, the Exchange Conversation Asset governs the weightingrules of engagement that apply to all the associated PortfolioConversation Assets and the Portfolio AI Entity Assets that have beencovered earlier for the individual asset classes. These weighting rulescan be governed by the Exchange and can be established for anypermutation of influence including:

Exchange Conversation Asset Feedback—this is treated in the same way asfor Portfolio Conversation Asset Feedback. The Exchange can deploy thesame Feedback standards across all or selected Portfolios or empowerselected Portfolios to deploy their own Feedback standards.

Exchange Conversation Asset Review—this is treated in the same way asfor Portfolio Conversation Asset Review. The Exchange can deploy thesame Review standards across all or selected Portfolios or empowerselected Portfolios to deploy their own Review standards.

Exchange Conversation Asset Outcomes—this is treated in the same way asfor Portfolio Conversation Asset Outcomes. The Exchange can deploy thesame Outcomes standards across all or selected Portfolios or empowerselected Portfolios to deploy their own Outcomes standards.

In one embodiment, further weightings applied in a similar way to theabove can be given to the following and again can be varied according toassociated variables: Exchange Conversation Display Advert, ExchangeConversation Widget, Exchange Conversation Event. An ExchangeConversation Asset can combine other variables such as country and anypermutation of the above to apply weightings to the ExchangeInteractions.

The approach to these weighting for Conversation Asset Interactions alsoapplied to the Conversation AI Entity Interactions, which can be treatedthe same or at a Exchange chosen variant.

The Exchange Weightings may not be applied to the monetary indexes as issimply a monetary actualization.

Example Exchange Conversation Liquidity Index

In one embodiment, the Exchange Conversation Liquidity Index monitorsthe trends for the accumulative monetary movements covering: ExchangeConversation Asset Monetary Index, Exchange Conversation AI EntityMonetary Index.

In one embodiment, as the Exchange Conversation Liquidity Index isupdated as monetary changes occur the Exchange Conversation LiquidityIndex can show trends by: hour, day, month, year.

In one embodiment, these trends can be drilled down into the ExchangeConversation Asset Monetary Index and the Exchange Conversation AIEntity Monetary Index. In turn these Indexes can be drill down into theactual transactions detailed earlier, including by Portfolio Assets.

In one embodiment, should the Exchange Conversation Liquidity Index bezero or indeed stagnates (no changes over time) then this means theExchange is illiquid.

Example Exchange Conversation Capital Index

In one embodiment, the Exchange Conversation Capital Index monitors thetrends for the accumulative asset share price movements covering:Exchange Conversation Assets, Exchange Conversation AI Entity Assets.

In one embodiment, the Exchange Conversation Capital Index changeswhenever portfolio assets are added or removed to the productionexchange and an asset share price has been applied conversation assetsare added or removed to the production exchange and an asset share pricehas been applied or conversation AI entity assets are added or removedto the production exchange and an asset share price has been applied oran asset share has been traded.

In one embodiment, the latest Asset Share Price used for a transactionis applied to all the Shares of the Asset: Total Asset Shares*LatestCurrent Share Price; the currency used is determined by the ExchangeOwner.

In one embodiment, the Exchange Conversation Capital Index is theaccumulative calculated share value for all the Assets within theExchange.

In one embodiment, the Exchange Conversation Capital Index can showtrends by: hour, day, month, year.

In one embodiment, these trends can be drilled down into the Asset Sharetransactions.

In one embodiment, should the Exchange Conversation Capital Index bezero then this means the Exchange has not been capitalized.

Example Exchange Conversation Future Index

In one embodiment, the Exchange Conversation Future Index is the futuretrend for the accumulation of the following: Exchange ConversationLiquidity Index, Exchange Conversation Capital Index. The ExchangeFuture=Exchange Conversation Liquidity Index+Exchange ConversationCapital Index and is calculated forward based on past trends coveringweekly, monthly and yearly projections. The Exchange Conversation FutureIndex can be adjusted by weightings over time set by the Exchange. Theprimary purpose of the Exchange Conversation Future Index is for AssetShare Investors and derivative trades.

In one implementation, forward projections are also calculated withExchange based adjustments for: Exchange Conversation Asset Index,Exchange Conversation Asset Interaction Index, Exchange ConversationAsset Monetary Index, Exchange Conversation AI Entity Performance Index,Exchange Conversation AI Entity Interaction Performance Index, ExchangeConversation AI Entity Monetary Performance Index, Exchange ConversationAI Entity Monetary Index.

In one embodiment, should the Exchange Conversation Future Index be zerothen this means the Exchange is illiquid.

Example Method for Asset Status

In one embodiment, the status of all Asset Classes includes:Production—status needed for trading and indexes, Pre-production,Withdrawn, Suspension, Archived, Deleted.

In one embodiment, the overriding sequence for changing status indescending order of influence is as follows: Exchange (higher levelaccreditation), Portfolio (lower level of accreditation), Individual(non accredited)

In one embodiment, if there are shares involving multiple ownershipassociated with a given Asset then the Asset cannot be Archived orDeleted until agreement has been reached with all shareholders.

In one embodiment, the Exchange and Portfolio can customize their ownrules for the Asset Status classes.

In one embodiment, if a Exchange Asset Class is Withdrawn, Suspended,Archived or Deleted that status applies to all Assets within its controland thus includes: Conversation Assets, Conversation AI Entity Assets,Portfolio Assets.

In one embodiment, if a Portfolio Asset Class is Withdrawn, Suspended,Archived or Deleted that status applies to all Assets within its controland thus includes: Conversation Assets, Conversation AI Entity Assets.

In one embodiment, within a Portfolio or Exchange an Asset Owner has theoption, subject to Portfolio and/or Exchange conditions to transfertheir Assets to another Exchange or Portfolio or indeed return tounaccredited status. However, should there be restriction clauses withthe Asset Shareholders Agreement that the Transfer cannot occur unlessthese conditions are satisfied.

In one embodiment, assets can be assigned a banned status by a Portfolioor an Exchange.

In one embodiment, assets can be assigned an age suitability status by aPortfolio or an Exchange.

In one embodiment, assets can be assigned restrictive access status by aPortfolio or an Exchange.

Example Method for Asset Account Management

In one embodiment, each individual and Asset have their own account thatcontain all access rights, authorization rights, approval rights,control rights, approval rights, share ownership rights and monetaryrights.

In one embodiment, the status of all Accounts includes:

Live

Suspension

Archived

Deleted

In one embodiment, the overriding sequence for changing status of anAccount in descending order of influence is as follows:

Exchange (higher level accreditation)

Portfolio (lower level of accreditation)

Individual (non accredited)

In one embodiment, an Account that has multiple owners cannot bearchived or deleted until agreement has been reached with all otherAccount holders.

In one embodiment, the Exchange and Portfolio can customize their ownrules for the Accounts within their own domain.

In one embodiment, within a Portfolio or Exchange an Account Owner hasthe option, subject to Portfolio and/or Exchange conditions to transfertheir Accounts to another Exchange or Portfolio or indeed return to nonPortfolio or Exchange status. However, should there be restrictionclauses with the Account Agreement that the Transfer cannot occur unlessthese conditions are satisfied.

In one embodiment, accounts can be assigned a minimum age forqualification but can be setup in conjunction with an authorized personasuch as lawyer, parent or guardian.

In one embodiment, accounts can support multiple currencies andsub-accounts such as reward bearing. Transfers between sub-accounts areallowable subject to Exchange or Portfolio Rules.

In one embodiment, the Exchange or Portfolio may impose restrictionsregarding transfers from the individual account.

In one embodiment, an Exchange or Portfolio may have a Prime Accountwhich automatically receives all or partial monetary value from accountswithin its domain. In some cases, the individual accounts within theirdomain can be regarded as Shadow Accounts. For example: an Exchange isowned by a Corporation that owns all the monies generated from theAssets but wants to retain Shadow Accounts for individual performance.

Example Method for Leveraging Anonymous Conversation Data

In one embodiment, the Conversation Data, as already covered is storedanonymously with other data tags such as Country Code.

In one embodiment, the ownership of this Conversational Data belongswith the Conversation Asset share ownership as already covered.

In one embodiment, however, the Portfolio and the Exchange can haveterms and conditions, which give them rights over the Anonymous Data inexchange for membership and/or monetization.

In one embodiment, a high level of semantic meaning the Portfolio and orthe Exchange may well set codification standards for the user generatedconversation and its use of Display Ads, Widgets and Events. Byestablishing the standards of these codes enables pick-up data to beobtained during the Digital Conversation. This Pick-up Data enableshigher forms of intelligence to be derived in context to actualConversational-Steps. When combining this Pick-up Data with theAnonymous Conversational Data could provide deep hindsights, insightsand foresights this increasing the value through aggregation across manydifferent types of Conversations.

In one embodiment, those Portfolios and Exchanges that establish thedeployment of the aggregation of data through their own standardizationincrease the probability of generating high forms of new value exchange.

Example Method for Short Learning Cycles

In one embodiment, the method for increasing the knowledge within aConversation Asset or a collection of Conversation Assets is based onthe following: Analysis of Digital Conversation Usage Patterns and theaggregation of Conversation-Strings, Analysis of Conversational Outcomesand Conversational End-Points, Analysis if timings associated withConversation-Steps, Feedback: structured or unstructured, Externalsources of influence.

In one embodiment, the Conversation Asset can be extended through:,Modification of script, Extension of script within the ConversationAsset, Extension of script through linking with New ConversationAsset(s), Extension through linking with other existing ConversationAssets.

In one embodiment, as the Conversation Asset when applied to knowledgeis an aggregation of ‘best’ human knowledge then when that knowledge isimmature or limited then the learning cycles can be relatively short aschanges are applied.

In one embodiment, the change controls are imposed within Portfolios andExchanges covering: empowered change with review checks, empoweredchanges with the option for reviews, controlled changes with enforcedreview or reviews

In one embodiment, changes are undertaken within a pre-productionstatus, which includes a test to ensure that the Conversation AI Entityand the Conversation Asset are synchronized without technical mishap.

In one embodiment, once the changes have been successfully applied thenthe respective Asset Negotiator or a delegated person has the authorityto release into production.

In one embodiment, the Digital Conversation is stored within the versionof the Asset change and is aggregated for the overall Asset. In thisway, comparison analysis can be undertaken to ascertain the impact thusaccelerating the learning cycles if appropriate.

In one embodiment, the script for Digital Conversations can berepresented in multiple languages. When multiple languages are presentthen checks are made when changes are made to ensure that the changesare applied to the other language derivatives.

Example Method for Finding the Best-Fit Digital Conversation

In one embodiment, the Portfolios and Exchanges can establish ataxonomic tree-based structure so that the Conversational Asset Authorcan link the Asset Wrapper to the final contextual node within thetaxonomic structure.

In one embodiment, where a Conversation Asset is best represented bymultiple taxonomic nodes then the method is reapplied multiple times.

In one embodiment, when multiple nodes are referenced then these areweighted to reflect the level of relevancy for a Digital Conversation.

In one embodiment, the Conversation Asset Author can extend theend-point Taxonomic Node with a customized taxonomic tree-structure toadvance the level of systemic precision.

In one embodiment, where there are more that one Conversation Assetassociated with an end-node or multiple-end node point then the list ofConversation Assets can be listed by the following: date & time ofcreation or last change, owner, author(s), accreditor(s), negotiator(s),AI entity, shareholder(s), feedback rating, inter exchanges—accreditedasset indexes including:, exchange conversation asset index, exchangeconversation asset interaction index, exchange conversation assetmonetary index, exchange conversation AI entity performance index,exchange conversation AI entity interaction performance index, exchangeconversation AI entity monetary performance index, exchange conversationAI entity monetary index, intra exchange portfolios—accredited assetindexes including: exchange portfolio conversation asset index, exchangeportfolio conversation asset interaction index, exchange portfolioconversation asset monetary index, exchange portfolio conversation AIentity performance index, exchange portfolio conversation AI entityinteraction performance index, exchange portfolio conversation AI entitymonetary performance index, exchange portfolio conversation AI entitymonetary index, portfolio—accredited asset indexes including portfolioconversation asset index, portfolio conversation asset interactionindex, portfolio conversation asset monetary index, portfolioconversation AI entity performance index, portfolio conversation AIentity interaction performance index, portfolio conversation AI entitymonetary performance index, portfolio conversation AI entity monetaryindex.

DCM-Platform Dialogue Agent Creation

FIG. 9 provides a logic flow diagram illustrating creating and capturingdialogues within embodiments of the DCM-Platform. In one embodiment, theconsumer may submit consumer dialogue contents to an AI agent (and/orDCM-Platform) 913 via a telephone call, an online chatting platform, amessenger, a social media platform, and/or the like, as discussed inFIG. 2A.

Within implementations, the AI agent may receive the dialogue responsefrom a consumer and perform data analysis. In alternativeimplementations, the DCM-Platform may receive a marketing request 901from a client and perform the data analysis to devise a marketing planfor the client 902. In one implementation, the DCM-Platform may create adialogue agent application based on the client needs 905

For example, a hair dresser manufacturer may submit a request to theDCM-Platform for AI marketing service for their new hair dresserproduct. The manufacturer may provide their marketing budget, productinformation, and/or the like to the DCM-Platform. The DCM-Platform maydetermine the number of AI agents to employ, the platform to deploy theAI agent, and create a dialogue agent accordingly.

The DCM-Platform may then populate the created dialogue agent on searchengines and social media 910 and implement the dialogue agent to captureconsumer-AI interactive dialogues 915, as further illustrated in FIGS.10A-11L.

In one implementation, the created dialogue agent application mayautomatically capture and request for client update 920, wherein theclient may provide updated product information 925, as furtherillustrated in FIG. 13. The dialogue agent may incorporate the updatedinformation 920 into the dialogue application, and devise interactivedialogue based marketing strategies 930, as further illustrated in FIGS.15A-F.

FIG. 10A-10F-3 provide diagrams illustrating creation of a dialogueagent application within embodiments of the DCM-Platform. In oneembodiment, to create a dialogue agent application, the DCM-Platform mayinitialize a dialogue agent based on client needs 1005, and launchdialogue tree visualization and dialogue script panel 1010. For example,as shown in FIG. 10B-C, a user interface comprising a split screen thatprovides dialogue tree visualisation and a dialogue script panel may beprovided, wherein the left half of the screen may provide a dialoguetree 1035 illustrating the evolution of dialogue steps, and the righthalf of the screen may illustrate the dialogue script 1306, includinginformation with regard to the dialogue agent 1037, subject 1038, keywords 1039, and/or the like

In one implementation, the DCM-Platform may generate dialogue scripts bycompleting a dialogue tree 1012, e.g., joining all the dots within adialogue tree as shown in FIG. 10D. For example, as shown in FIG. 10D, adot 1041 in the dialogue tree may comprise a dialogue line from the AIagent “Hi, this is your stylist . . . ”, and an ending dot 1042comprises a line “Thanks and see you.” The dialogue may be consideredcomplete when an ending dot 1042 is connected in the dialogue tree.

In one implementation, upon completing a dialogue tree, the DCM-Platformmay set social media parameters for the dialogue agent 1016. Forexample, as shown in FIG. 10E, the DCM-Platform may add dialogue agent1045 to a variety of social media platforms, such as, but not limited toTiny URL, FOLLOW ME, Twitter, Facebook, Blogger, LinkedIn, Tell Wiki,Mobile, and/or the like. In one implementation, the DCM-Platform mayconfigure the social media parameters based on client requests. Inalternative implementations, the DCM-Platform may determine the socialmedia deployment based on client marketing budget.

In one implementation, the DCM-Platform may create dialogue agentapplication 1018, which may be implemented via automatically generatinga web-service 1018(a), automatically connecting the dialogue web-serviceto an avatar front end 1018(b), based on which a dialogue agentapplication may be completed 1018(c).

In a further implementation, the dialogue agent application may becreated within a dialogue cloud with key words which may be picked up bysearch engines (e.g., Bing, Yahoo, Google, etc.) 1020(a). For example,as shown in FIG. 10F-1, the dialogue script discussed in FIGS. 10B-E maybe associated with a keyword “hairdresser,” which may be populated ontoGoogle search for products, services related to “hairdresser” for the AIagent “Natalie” 1050, and the AI agent “Natalie” may in turn utilize thesearch results to generate dialogue lines to provide information withregard to the “hairdresser” to a consumer.

In another further implementation, the dialogue agent may be populatedonto social media platforms 1020(b). For example, FIG. 10F-2 illustratesan automated population of a micro logging and social networking service(i.e., Twitter) using a shortened URL (e.g., Tiny URL, etc.).

In another further implementation, the dialogue agent may create mobileapplications accessible from the internet and smart phone applications(e.g., Apple iPhone, Blackberry, Evo, etc.). For example, as shown inFIG. 10F-3, a dialogue agent avatar 1055 may be displayed on aconsumer's smart phone, and a list of Internet search results on relatedproducts and/or services 1060 may be displayed in contextual adds-onalongside the dialogue avatar.

Upon completing creation a dialogue agent application, the DCM-Platformmay also generate wrapper description identification 1020(d) of thedialogue agent application. For example, the wrapper of a conversationasset, an AI entity asset, a portfolio asset, and/or an exchange assetthat contains the created AI agent application may be updated with thedescription of the application accordingly.

In a further implementation, the DCM-Platform may register the generatedAI agent application on the virtual asset exchange platform 1022, andthe financial trading platform 1024, by generating a wrapper for theagent application as described within embodiments of FIGS. 4B-7C.

FIG. 11A provides a logic flow illustrating generating an intelligentdialogue within embodiments of the DCM-Platform. In one embodiment, tostart a dialogue and/or to respond to a consumer submitted dialogueline, the dialogue agent may retrieve a dialogue line 1105 from thedialogue application. The dialogue application may determine whether theon-going dialogue contains an If-Then-Else logic 1108.

If there is an If-Then-Else logic, the agent may retrieve options forthe conditional logic 1115, and determines whether the consumersubmitted dialogue step contains an outcome. If there is an outcome, theagent may select a verbal outcome for each option to present to theconsumer 1118. Otherwise, the agent may resort to a search engine togenerate a hyperlink outcome for the consumer 1119, and/or direct theconsumer to another AI agent to continue the conversation.

For example, as shown in FIG. 11B, the dialogue agent may receive twopotential responses from a consumer “confirm appointment” 1130 or“cannot attend” 7 1135, each associated with a response 1136 and 1137 asshown in FIG. 11C. In another example, as shown in FIG. 11D, thedialogue agent may generate a hyperlink 1140, e.g., to suggest theconsumer reschedule the appointment. In another example, as shown inFIG. 11E, the dialogue agent may provide a hyperlink to direct theconsumer to another AI agent “John” 1142.

In one implementation, to help optimise conventional search, thedialogue agent may determine whether a search is requested in theconversation 1120, e.g., whether a consumer inquiry is received, and/oran aid is available to capture search logic, outputs and comments withthe dialogue agent. In one implementation, the dialogue agent maypopulate key words onto a search engine (e.g., Google, etc.) forresults, and generate a dialogue line for the consumer based on theGoogle search results 1123.

In one implementation, search engine may not return desirable results.For example, FIG. 11F illustrates a dialogue search that Google Searchfailed to match the search need, wherein the agent's search on “hairsalon and stylist” in “Maldon, Essex, UK” does not return any result. Asshown in FIG. 11G, the dialogue agent may generate a dialogue line basedon partial key words search results when Google search failed 1122. Forexample, as shown in FIG. 11G, when the Google search “hairdresserMaldon Essex hair extension” fails to return desirable results, thedialogue agent may generate a link comprising a list of localhairdressers 1160.

In an alternative implementation, the dialogue agent may providealternate questions to the consumer to obtain information 1125. Forexample, as shown in FIG. 11H, the dialogue agent may generate a line“what type of hair specialist would you like” to obtain furtherinformation to narrow down the search 1165, and thus provide relevantsearch results based on consumer provided preferences 1170 as shown inFIG. 11I.

In one implementation, the dialogue agent may then update an assetwrapper with the generated search results and the dialogue lines 1127.

FIGS. 11J-L further illustrate generating a dialogue comprising anIf-Then-Else logic within embodiments of the DCM-Platform. FIG. 11J-Kprovide an exemplar user interface screen for dialogue agent creation.

In one implementation, as shown in FIG. 11J-K, a dialogue agentapplication developer may create a dialogue logic by building a decisiontree associated with search engine results. For example, a dialogue line“Do you want to know about the cheapest battery charger?” may begenerated as a dialogue step for a consumer as the node “1” in thedecision tree; two conditional responses from the consumer “Yes” and“No” are associated with this question, and thus form a bipartitebranches “2” and “3” in the decision tree. For each branch, the dialogueagent may associate a search result link to be incorporated as adialogue response for the conditional branch.

In one implementation, the dialogue builder may be created by a humandeveloper. In another implementation, the dialogue applications may forman Internet community to allow Wiki submission of dialogue lines andconditions.

In one implementation, the search associated with each dialogue step maybe refined progressively based on the consumer submitted feedback. Forexample, as shown in FIG. 11L, the dialogue agent may start a query on“best battery chargers,” when the consumer triggers the branch “Yes”;the search may be refined to a query on “D-size best battery charger”when the consumer triggers the conditional branch by indicating“D-size.”

For example, in one implementation, an exemplar XML implementation of anIf-Then-Else logic in the dialogue may take a form similar to:

if cheapest_batter_charger=“yes” display the following text, “are youinterested in D size battery chargers?” query www.google.com “cheapestbattery charger” if cheapest_batter_charger=“NO” display the followingtext, “Are you interested in the best battery chargers.” querywww.google.com “best battery charger” if D-size_battery=“Yes” displaythe following text, “please visit www.d- size_battery.com/....” ifD-size_battery=“No” display the following text, “Thank you for visitingour website.” ... end if statements

In a further implementation, the DCM-Platform may facilitate a consumerto search for an available dialogue agent in a similar manner asdiscussed in FIG. 11L. For example, a consumer may submit “batterycharger,” and the DCM-Platform may prompt a search on its database for adialogue agent that can assist on topics related to “battery chargers.”

FIGS. 12A-12D provide diagrams illustrating dialogue analytics withinembodiments of the DCM-Platform. In one embodiment, the dialogue agentmay initiate dialogue analytics to drive the consumer-AI interaction1205. For example, the dialogue agent may retrieve recorded dialogueactions in related topics 1210, including dialogue action recordedanonymously for large scale analytics 1210(a), linked to user forprofiling analytics 1210(b), and/or linked to dialogue agent for valueanalytics 1210(c).

The dialogue agent may then determine a dialogue pathway of theretrieved dialogue 1215. For example, FIGS. 12B(a)-(d) illustrateexamples of pathways taken by a consumer interacting with a dialogueagent, wherein each node denotes a dialogue action/line in the dialoguetree discussed in FIG. 10C. For example, FIG. 12B(a) shows a dialoguepathway wherein the consumer terminated the interaction before reachingan outcome.

Based on the dialogue pathway, the dialogue agent may determine dialogueparameters 1220, such as, but not limited to an actual number ofdialogue actions in the interaction 1220(a), an amount of time taken foreach dialogue-action 1220(b), and/or the like. For example, as shown inFIG. 12B(c), the number of dialogue actions may be the number of edgesalong a dialogue pathway, and the amount of time for eachdialogue-action is illustrated in FIG. 12B(d).

In one implementation, the dialogue agent may determine whether multipleconsumers, and/or multiple dialogue pathways are included in thedialogue. IF yes, the dialogue analytics may aggregate decision-pathwaysacross multiple consumers interacting with the dialogue agent 1225, asshown in FIG. 12C.

The dialogue agent may further analyze value of the dialogue based onthe parameters, pathways of the dialogue 1230, and update the relatedasset wrapper accordingly. FIG. 12D provide an exemplary screen shotillustrating a visualisation with multiple dimensions of dialogueanalytics within embodiments of the DCM-Platform.

FIG. 13 illustrates an exemplar diagram illustrating capturing clientupdate within embodiments of the DCM-Platform. For example, a dialogueagent's knowledge may be updated, via incorporating search results,and/or the like. As shown in FIG. 13, the dialogue agent may capture newinformation related to the client while performing searches on a searchengine (e.g., Google, etc.) 1305, and then send a request to the client1310 for updated product information, so that the dialogue agent mayincorporate the new information into the dialogue application toadvertise it to consumers.

FIGS. 14A-B illustrate exemplar user interfaces within embodiments ofthe DCM-Platform. In one embodiment, a DCM-Platform user, e.g., an AIadvertising company employee, a dialogue agent application developer,etc., may operate the dialogue applications with a personalised actionbar 1405 as shown in FIG. 14A. In one implementation, the action bar1405 may comprise a “My Hub” 1410 as a way of monitoring activity andtasks, a dialogue analytics button 1415 for dialogue pathway analysis, alist of generated dialogue agents, a drop down list of dialogueactivities in foreign languages 1420, and/or the like.

In another implementation, the “My Hub” application 1410 may provide adashboard view for the DCM-Platform users to track activities of thedialogue agents and the associated interactions with the consumers. Forexample, FIG. 14B shows the “My Hub” feature may show “My Followers”1430 from social media platforms, a list of “My dialogue Agents” 1435, alist of feedback alerts 1440, a list of dialogue agent research ondifferent topics and searches 1445, a chart illustrating internationaldialogue agent performance 1450, a list of notes on captured Googlesearches and outputs 1455, and/or the like.

FIGS. 15A-E provide diagrams illustrating various implementations ofinteractive marketing via DCM-Platform. In one implementation, business,such as manufacturers, retailers, service providers, and/or the like,may use the dialogue agents to sell and support products via web-basedmarketing, as shown in FIG. 15A. For example, web-based search engines,such as Yahoo, Google, Bing, etc., may retrieve key words from thedialogue agents and feed search results including advertised productsinformation to the dialogue agents.

In a further implementation, interactive marketing may be realized viaInternet communities. For example, the DCM-Platform may use Internetcommunities, recommendation engines and services, and social networks(e.g., Stumble Upon, Digg, etc.) to stimulate global networking offavourite dialogue agents, e.g., by selecting related topics via StumbleUpon as shown in FIG. 15B.

In another example, each dialogue agent may have its own social mediaidentity (e.g., Twitter, eBlogger, etc.) and followers, and thus formfeedback loops from its followers automatically linked to Twitter, asshown in FIG. 15C. In this way, the dialogue agent and/or theDCM-Platform may revise the marketing plan, e.g., the content, language,presentation, format, of the dialogue, etc., based on consumer feedbackson a real-time basis.

In one implementation, when a consumer has an activity via the socialmedia, e.g., update his status indicating a demand of service “hairextension,” as shown in FIG. 15D, the dialogue agents may receive thestatus update and automatically generate dialogue lines providinginformation of “hair extension” services featuring hair salons which maybe advertising clients of the DCM-Platform. For another example, thedialogue agents may communicate via social networks to update theirstored knowledge and information, as shown in FIG. 15D. Thus dialogueagents and consumers may form a community and group on social mediaplatforms to offer advice and share knowledge of brand products andservices.

In a further implementation, authors of dialogue agents may use theirblogs for publishing details about their advancements and interactions.In a further implementation, the DCM-Platform may connect to Wikis(e.g., Wikipedia, etc.) to include dialogue agents that are relevant toa subject matter, e.g., a dialogue wiki application. For example, asshown in FIG. 15E, the Wikipedia entry of the founder of Artificialintelligence 1535, an AI dialogue agent 1540 may be associated with theWikipedia entry to provide interactive knowledge to a reader. Forexample, a reader may ask questions with regard to the topic, e.g.,“what are major academic journals on artificial intelligence?”, etc.,and the dialogue agent 1540 may then generate answers to the reader.

In a further implementation, the DCM-Platform may form a dialogue agentapplication community to build dialogue agent applications, enhanceexisting applications with dialogue agents and/or the like. For example,the dialogue agent applications may be sold on an Internet store, e.g.,the iTunes store, etc., and business seeking for advertising servicesmay purchase dialogue agent applications for marketing plan executions.

FIGS. 16A-D provide diagrams illustrating dialogue knowledgeaccumulation within embodiments of the DCM-Platform.

FIG. 16A provides an example dialogue for medical assistance withinembodiments of the DCM-Platform. In one embodiment, as shown in FIG.16A, a dialogue between a consumer and a medical consultant dialogueagent may start with the dialogue agent sending greetings and requestingthe consumer select a symptom 1605. For example, the consumer may selectwhether he has developed a fever.

The dialogue agent may further provide instructions to describe symptoms1608, e.g., to explain what is a fever to the consumer. If the consumerindicates a fever, the dialogue agent may respond “Do not worry” andrequest the consumer select an age status 1615, e.g., whether theconsumer is under 12 years old. If yes, the dialogue agent may directthe conversation to a pediatrician dialogue agent 1620. Otherwise, thedialogue agent may link to a knowledge database and provide medicalinstructions on fever to the consumer 1625. In a further implementation,the dialogue agent may generate a search list of physician contacts tothe consumer.

In another implementation, if the consumer does not select fever, thedialogue agent may direct the consumer to a physician dialogue agent forfurther assistance 1630, or suggest the consumer see a physician andprovide a list of physician contacts.

In one embodiment, the DCM-Platform may create ecosystems of a new typeof virtual agent application that enables just-in-time knowledge. Forexample, each virtual agent application has its' own decision-treecontaining scripted dialogue that can be “dynamically linked” to otherapplications, which facilitates the knowledge acquirer to reach theirspecific relevant, targeted outcomes, as shown in FIG. 16B.

In one implementation, whereas search is barely a one-step interaction.these virtual agent applications use a combination of natural andscripted language for a meaningful conversation with consumers includingdecision outcomes, as shown in FIG. 16C.

As shown in FIG. 16C, when a virtual agent application engages inconversation, the acquirer interacts with a dialogue-step at a time sothey only ‘see’ the selected pathway, e.g., a pathway selected by theconsumer (FIG. 16B(a)). Each conversation is captured in adecision-string, as shown in FIG. 16B(b). In one implementation, thedialogue with a person is streamlined along a decision-pathway that canbe as long or short as needed and, if necessary based on questionsanswered, one virtual agent can automatically hand off to anothervirtual agent on a different decision-string with more relevantknowledge, and a successful dialogue may end with a decision-outcome andthus presents the optimal point for monetization, as shown in FIG.16B(b).

In one embodiment, the DCM-Platform may obtain and store knowledge toform a world knowledge bank, e.g., a knowledge database, as shown inFIG. 16D.

For example, each virtual agent app may have an API link with the worldknowledge bank for access to the latest version of their knowledge, therecording of their dialogue and the orchestration of events such asadverts and transactions. The knowledge bank may be monetized throughvirtual agent apps across markets.

For example, via the knowledge bank, DCM-Platform may provide knowledgedelivery as professional advisory services by virtual agent apps acrossglobal health in paramedical, world trade paralegal and world tradeaccounting services, and/or the like; and establish consumer marketretail brands provide knowledge delivery through virtual agent apps forconsumers across consumables including electronics (e.g. digitalcameras), white goods, clothing, travel, etc. leading to smarter onlinetransactions.

In further implementations, the DCM-Platform may monetize the knowledgebank with revenues generated from dialogue advertising, includingmultimedia advertisement at each dialogue-step, tariffs on high qualityknowledge exceed the price-per-display, price-per-click andlocation-based pricing CPM rates, and/or the like. The DCM-Platform mayfurther generate revenue from Dialogue Analytics for businessintelligence (value from emergent dialogue, patterns and flows),Transactions Commissions (dialogue transaction commission perdialogue-step, microfinance administration charges), corporate services(subscription charges to access knowledge portfolios, licensed revenuesthrough virtual agent platforms, corporate internal knowledge exchange:priced per conversation), knowledge stock exchanges (trading of virtualagent app shares—several owners of each virtual agent, pass-thrutransactions such as a financial products, derivatives, securities),and/or the like.

Alternative Embodiments of Dialogue Agent Applications

Further implementations of the DCM-Platform may include a white-boxartificial intelligence engine associated with a dialogue avatar. The AIengine may support advertisement inventory for each dialogue-action, andan API may be created to link with an advertisement engine enablingdynamic ad placement and pricing.

For another example, The AI Engine may support media placement forselective dialogue-actions, and placement of movement codes forselective dialogue-actions.

In another implementation, the AI engine may support placement ofsemantic codes for selective dialogue-actions, wherein the semanticcodes provides the basis for semantic analytics to generate greaterinsights and learning. The AI engine may further support placement ofecommerce codes for selective dialogue-actions.

In one implementation, the AI engine may generate ecommerce codes usedto orchestrate 3^(rd) party ecommerce services for a targeted product orservice. The AI engine may further be extended with an API to linkdialogue agents into virtual communities for 7/24 accessibility.

In further implementations, the AI engine may support automated handoverto another dialogue-tree, which facilitates an infinite number ofdialogue pathways to be created and captured during the interaction

In further implementations, the DCM-Platform may comprise newadvertisement inventory across all digital end users; useDialogue-Action as a new universal currency for measurement; empowersusers to create dialogue agent apps; create new earning asset forauthors; orchestrate sponsorship and advertisements;

orchestrate ecommerce; orchestrate media; establish foundation forknowledge assets, and/or the like.

In some embodiments the DCM-Platform may optimises search by creatingDialogue Agents that are driven by human powered artificialintelligence; In some embodiments, the DCM-Platform may provideincentives to maximize the population of a dialogue wiki, dialogueagents, dialogue agent avatars, and dialogue agent applications acrossclouds, mobile operators, networked marketing, networked marketing andnetworked marketing, and social networks, in order to maximise highestvolume population outcomes.

In some implementations, a percentage of the links generated by thedialogue agents may have referral links that give money or incentive‘value’ points and/or prizes.

In some implementations, the dialogue agent may confirm userunderstanding and compliance via interactive user feedback, rewardmechanisms, and/or the like.

In some implementations, the dialogue wiki, dialogue agents, dialogueagent avatars, and dialogue agent applications may be aggregated andanalyzed for user data, characteristics, tutorial adoption, userinteractive feedback such as asking “how was your purchase,” systemusage, user behaviour(s) and/or the like, and structurepay-for-performance incentives based on the intelligence for variousentities participating in providing products and/or services for systemusers.

DCM-Platform Components

FIG. 17 illustrates an implementation of DCM-Platform components in oneembodiment of DCM-Platform operation. A DCM-Platform apparatus 1701 maycontain a number of processing components and/or data stores. ADCM-Platform controller 1705 may serve a central role in someembodiments of DCM-Platform operation, serving to orchestrate thereception, generation, and distribution of data and/or instructions to,from and between target device(s) and/or client device(s) viaDCM-Platform modules and in some instances mediating communications withexternal entities and systems.

In one embodiment, the DCM-Platform controller 1705 may be housedseparately from other modules and/or databases within the DCM-Platformsystem, while in another embodiment, some or all of the other modulesand/or databases may be housed within and/or configured as part of theDCM-Platform controller. Further detail regarding implementations ofDCM-Platform controller operations, modules, and databases is providedbelow.

In one embodiment, the DCM-Platform Controller 1705 may be coupled toone or more interface components and/or modules. In one embodiment, theDCM-Platform Controller may be coupled to a communications module 1730and communications input/output (I/O) interface 1735. a maintenanceinterface 212, and a power interface 214. The user interface 1738 may beconfigured to receive user inputs and display application states and/orother outputs. The UI may, for example, allow a user to adjustDCM-Platform system settings, select communication methods and/orprotocols, engage mobile device application features and/or the like. Inone implementation, the user interface 1738 may include, but not limitedto devices such as, keyboard(s), mouse, stylus(es), touch screen(s),digital display(s), and/or the like.

In one embodiment, the DCM-Platform Controller 205 may further becoupled to a communications module 1730, configured to interface withand/or process signals from communications I/O components 1735. Thecommunications I/O components 1735 may comprise components facilitatingtransmission of electronic communications via a variety of differentcommunication protocols and/or formats as coordinated with and/or by thecommunications module 1730. Communication I/O components 1735 may, forexample, contain ports, slots, antennas, amplifiers, and/or the like tofacilitate transmission of user interactive dialogue feedbacks, Internetsearch results, via any of the aforementioned methods. Communicationprotocols and/or formats for which the communications module 1730 and/orcommunications IO components 1735 may be compatible may include, but arenot limited to, GSM, GPRS, W-CDMA, CDMA, CDMA2000, HSDPA, Ethernet,WiFi, Bluetooth, USB, and/or the like. In various implementations, thecommunication I/O 235 may, for example, serve to configure data intoapplication, transport, network, media access control, and/or physicallayer formats in accordance with a network transmission protocol, suchas, but not limited to FTP, TCP/IP, SMTP, Short Message Peer-to-Peer(SMPP) and/or the like. The communications module 1730 andcommunications I/O 1735 may further be configurable to implement and/ortranslate Wireless Application Protocol (WAP), VoIP and/or the like dataformats and/or protocols. The communications I/O 1735 may further houseone or more ports, jacks, antennas, and/or the like to facilitate wiredand/or wireless communications with and/or within the DCM-Platformsystem. For instance, in the above example, the DCM-Platform controller1705 may transmit the generated dialogue actions to the communicationmodule 1730, and the dialogue actions may then be transmitted toexternal entities (e.g., an AI entity, or a consumer, etc.) through thecommunications I/O 1735.

Numerous data transfer protocols may also be employed as DCM-Platformconnections, for example, TCP/IP and/or higher protocols such as HTTPpost, FTP put commands, and/or the like. In one implementation, thecommunications module 1730 may comprise web server software equipped toconfigure application state data for publication on the World Wide Web.Published application state data may, in one implementation, berepresented as an integrated video, animation, rich internetapplication, and/or the like configured in accordance with a multimediaplug-in such as Adobe Flash. In another implementation, thecommunications module 1730 may comprise remote access software, such asCitrix, Virtual Network Computing (VNC), and/or the like equipped toconfigure application state data for viewing on a remote client (e.g., aremote display device).

In one embodiment, the DCM-Platform Controller may further be coupled toa Dialogue Generator 1715, a Social Media Synchronizer 1716, a KnowledgeBuilder 1718, an Asset Generator 1719, a Conversation Monetizer 1720and/or the like. Within various implementations, the Dialogue Generator1715 may receive and process consumer dialogue requests, and generateinteractive dialogue actions. The generated dialogues may be populatedand implemented via a virtual conversation AI entity on a social mediaplatform by the Social Media Synchronizer 1716. The Knowledge Builder1718 may perform data mining over the stored interactive dialoguescripts, and obtain various information from a client (e.g., brandinformation, product information, etc.) to synthesize information andstore in the Knowledge database 1752. In one implementation, the AssetGenerator 1719 may encapsulate the digital conversation and createconversation assets, AI entity assets, portfolio assets, and/or exchangeassets for trades, and the Conversation Monetizer 1720 may determine thevalue of each asset.

In one implementation, the DCM-Platform controller 1705 may further becoupled to a plurality of databases configured to store and maintainDCM-Platform data, such as but not limited to a Client database 1740, aConsumer database 1742, an AI Agent database 1744, an Asset database1746, a Transaction database 1748, a Scripts database 1750, a Knowledgedatabase 1752, and/or the like, as further illustrated in FIG. 18.

DCM-Platform Controller

FIG. 18 shows a block diagram illustrating embodiments of a DCM-Platformcontroller. In this embodiment, the DCM-Platform controller 1801 mayserve to aggregate, process, store, search, serve, identify, instruct,generate, match, and/or facilitate interactions with a computer throughartificial intelligence technologies, and/or other related data.

Typically, users, which may be people and/or other systems, may engageinformation technology systems (e.g., computers) to facilitateinformation processing. In turn, computers employ processors to processinformation; such processors 1803 may be referred to as centralprocessing units (CPU). One form of processor is referred to as amicroprocessor. CPUs use communicative circuits to pass binary encodedsignals acting as instructions to enable various operations. Theseinstructions may be operational and/or data instructions containingand/or referencing other instructions and data in various processoraccessible and operable areas of memory 1829 (e.g., registers, cachememory, random access memory, etc.). Such communicative instructions maybe stored and/or transmitted in batches (e.g., batches of instructions)as programs and/or data components to facilitate desired operations.These stored instruction codes, e.g., programs, may engage the CPUcircuit components and other motherboard and/or system components toperform desired operations. One type of program is a computer operatingsystem, which, may be executed by CPU on a computer; the operatingsystem enables and facilitates users to access and operate computerinformation technology and resources. Some resources that may beemployed in information technology systems include: input and outputmechanisms through which data may pass into and out of a computer;memory storage into which data may be saved; and processors by whichinformation may be processed. These information technology systems maybe used to collect data for later retrieval, analysis, and manipulation,which may be facilitated through a database program. These informationtechnology systems provide interfaces that allow users to access andoperate various system components.

In one embodiment, the DCM-Platform controller 1801 may be connected toand/or communicate with entities such as, but not limited to: one ormore users from user input devices 1811; peripheral devices 1812; anoptional cryptographic processor device 1828; and/or a communicationsnetwork 1813.

Networks are commonly thought to comprise the interconnection andinteroperation of clients, servers, and intermediary nodes in a graphtopology. It should be noted that the term “server” as used throughoutthis application refers generally to a computer, other device, program,or combination thereof that processes and responds to the requests ofremote users across a communications network. Servers serve theirinformation to requesting “clients.” The term “client” as used hereinrefers generally to a computer, program, other device, user and/orcombination thereof that is capable of processing and making requestsand obtaining and processing any responses from servers across acommunications network. A computer, other device, program, orcombination thereof that facilitates, processes information andrequests, and/or furthers the passage of information from a source userto a destination user is commonly referred to as a “node.” Networks aregenerally thought to facilitate the transfer of information from sourcepoints to destinations. A node specifically tasked with furthering thepassage of information from a source to a destination is commonly calleda “router.” There are many forms of networks such as Local Area Networks12 (LANs), Pico networks, Wide Area Networks (WANs), Wireless Networks(WLANs), etc.

For example, the Internet is generally accepted as being aninterconnection of a multitude of networks whereby remote clients andservers may access and interoperate with one another.

The DCM-Platform controller 1801 may be based on computer systems thatmay comprise, but are not limited to, components such as: a computersystemization 1802 connected to memory 1829.

Computer Systemization

A computer systemization 1802 may comprise a clock 1830, centralprocessing unit (“CPU(s)” and/or “processor(s)” (these terms are usedinterchangeable throughout the disclosure unless noted to the contrary))1803, a memory 1829 (e.g., a read only memory (ROM) 1806, a randomaccess memory (RAM) 1805, etc.), and/or an interface bus 1807, and mostfrequently, although not necessarily, are all interconnected and/orcommunicating through a system bus 1804 on one or more (mother)board(s)1802 having conductive and/or otherwise transportive circuit pathwaysthrough which instructions (e.g., binary encoded signals) may travel toeffectuate communications, operations, storage, etc. The computersystemization may be connected to a power source 1886; e.g., optionallythe power source may be internal. Optionally, a cryptographic processor1826 and/or transceivers (e.g., ICs) 1874 may be connected to the systembus. In another embodiment, the cryptographic processor and/ortransceivers may be connected as either internal and/or externalperipheral devices 1812 via the interface bus I/O. In turn, thetransceivers may be connected to antenna(s) 1875, thereby effectuatingwireless transmission and reception of various communication and/orsensor protocols; for example the antenna(s) may connect to: a TexasInstruments WiLink WL1283 transceiver chip (e.g., providing 802.11n,Bluetooth 3.0, FM, global positioning system (GPS) (thereby allowingDCM-Platform controller to determine its location)); BroadcomBCM4329FKUBG transceiver chip (e.g., providing 802.11n, Bluetooth2.1+EDR, FM, etc.); a Broadcom BCM4750IUB8 receiver chip (e.g., GPS); anInfineon Technologies X-Gold 618-PMB9800 (e.g., providing 2G/3GHSDPA/HSUPA communications); and/or the like. The system clock typicallyhas a crystal oscillator and generates a base signal through thecomputer systemization's circuit pathways. The clock is typicallycoupled to the system bus and various clock multipliers that willincrease or decrease the base operating frequency for other componentsinterconnected in the computer systemization. The clock and variouscomponents in a computer systemization drive signals embodyinginformation throughout the system. Such transmission and reception ofinstructions embodying information throughout a computer systemizationmay be commonly referred to as communications. These communicativeinstructions may further be transmitted, received, and the cause ofreturn and/or reply communications beyond the instant computersystemization to: communications networks, input devices, other computersystemizations, peripheral devices, and/or the like. It should beunderstood that in alternative embodiments, any of the above componentsmay be connected directly to one another, connected to the CPU, and/ororganized in numerous variations employed as exemplified by variouscomputer systems.

The CPU comprises at least one high-speed data processor adequate toexecute program components for executing user and/or system-generatedrequests. Often, the processors themselves will incorporate variousspecialized processing units, such as, but not limited to: integratedsystem (bus) controllers, memory management control units, floatingpoint units, and even specialized processing sub-units like graphicsprocessing units, digital signal processing units, and/or the like.Additionally, processors may include internal fast access addressablememory, and be capable of mapping and addressing memory 1829 beyond theprocessor itself; internal memory may include, but is not limited to:fast registers, various levels of cache memory (e.g., level 1, 2, 3,etc.), RAM, etc. The processor may access this memory through the use ofa memory address space that is accessible via instruction address, whichthe processor can construct and decode allowing it to access a circuitpath to a specific memory address space having a memory state. The CPUmay be a microprocessor such as: AMD's Athlon, Duron and/or Opteron;ARM's application, embedded and secure processors; IBM and/or Motorola'sDragonBall and PowerPC; IBM's and Sony's Cell processor; Intel'sCeleron, Core (2) Duo, Itanium, Pentium, Xeon, and/or XScale; and/or thelike processor(s). The CPU interacts with memory through instructionpassing through conductive and/or transportive conduits (e.g., (printed)electronic and/or optic circuits) to execute stored instructions (i.e.,program code) according to conventional data processing techniques. Suchinstruction passing facilitates communication within the DCM-Platformcontroller and beyond through various interfaces. Should processingrequirements dictate a greater amount speed and/or capacity, distributedprocessors (e.g., Distributed DCM-Platform), mainframe, multi-core,parallel, and/or super-computer architectures may similarly be employed.Alternatively, should deployment requirements dictate greaterportability, smaller Personal Digital Assistants (PDAs) may be employed.

Depending on the particular implementation, features of the DCM-Platformmay be achieved by implementing a microcontroller such as CAST'sR8051XC2 microcontroller; Intel's MCS 51 (i.e., 8051 microcontroller);and/or the like. Also, to implement certain features of theDCM-Platform, some feature implementations may rely on embeddedcomponents, such as: Application-Specific Integrated Circuit (“ASIC”),Digital Signal Processing (“DSP”), Field Programmable Gate Array(“FPGA”), and/or the like embedded technology. For example, any of theDCM-Platform component collection (distributed or otherwise) and/orfeatures may be implemented via the microprocessor and/or via embeddedcomponents; e.g., via ASIC, coprocessor, DSP, FPGA, and/or the like.Alternately, some implementations of the DCM-Platform may be implementedwith embedded components that are configured and used to achieve avariety of features or signal processing.

Depending on the particular implementation, the embedded components mayinclude software solutions, hardware solutions, and/or some combinationof both hardware/software solutions. For example, DCM-Platform featuresdiscussed herein may be achieved through implementing FPGAs, which are asemiconductor devices containing programmable logic components called“logic blocks”, and programmable interconnects, such as the highperformance FPGA Virtex series and/or the low cost Spartan seriesmanufactured by Xilinx. Logic blocks and interconnects can be programmedby the customer or designer, after the FPGA is manufactured, toimplement any of the DCM-Platform features. A hierarchy of programmableinterconnects allow logic blocks to be interconnected as needed by theDCM-Platform system designer/administrator, somewhat like a one-chipprogrammable breadboard. An FPGA's logic blocks can be programmed toperform the operation of basic logic gates such as AND, and XOR, or morecomplex combinational operators such as decoders or mathematicaloperations. In most FPGAs, the logic blocks also include memoryelements, which may be circuit flip-flops or more complete blocks ofmemory. In some circumstances, the DCM-Platform may be developed onregular FPGAs and then migrated into a fixed version that more resemblesASIC implementations. Alternate or coordinating implementations maymigrate DCM-Platform controller features to a final ASIC instead of orin addition to FPGAs. Depending on the implementation all of theaforementioned embedded components and microprocessors may be consideredthe “CPU” and/or “processor” for the DCM-Platform.

Power Source

The power source 1886 may be of any standard form for powering smallelectronic circuit board devices such as the following power cells:alkaline, lithium hydride, lithium ion, lithium polymer, nickel cadmium,solar cells, and/or the like. Other types of AC or DC power sources maybe used as well. In the case of solar cells, in one embodiment, the caseprovides an aperture through which the solar cell may capture photonicenergy. The power cell 1886 is connected to at least one of theinterconnected subsequent components of the DCM-Platform therebyproviding an electric current to all subsequent components. In oneexample, the power source 1886 is connected to the system bus component1804. In an alternative embodiment, an outside power source 1886 isprovided through a connection across the I/O 1808 interface. Forexample, a USB and/or IEEE 1394 connection carries both data and poweracross the connection and is therefore a suitable source of power.

Interface Adapters

Interface bus(ses) 1807 may accept, connect, and/or communicate to anumber of interface adapters, conventionally although not necessarily inthe form of adapter cards, such as but not limited to: input outputinterfaces (I/O) 1808, storage interfaces 1809, network interfaces 1810,and/or the like. Optionally, cryptographic processor interfaces 1827similarly may be connected to the interface bus. The interface busprovides for the communications of interface adapters with one anotheras well as with other components of the computer systemization.Interface adapters are adapted for a compatible interface bus. Interfaceadapters conventionally connect to the interface bus via a slotarchitecture. Conventional slot architectures may be employed, such as,but not limited to: Accelerated Graphics Port (AGP), Card Bus,(Extended) Industry Standard Architecture ((E)ISA), Micro ChannelArchitecture (MCA), NuBus, Peripheral Component Interconnect (Extended)(PCI(X)), PCI Express, Personal Computer Memory Card InternationalAssociation (PCMCIA), and/or the like.

Storage interfaces 1809 may accept, communicate, and/or connect to anumber of storage devices such as, but not limited to: storage devices1814, removable disc devices, and/or the like. Storage interfaces mayemploy connection protocols such as, but not limited to: (Ultra)(Serial) Advanced Technology Attachment (Packet Interface) ((Ultra)(Serial) ATA(PI)), (Enhanced) Integrated Drive Electronics ((E)IDE),Institute of Electrical and Electronics Engineers (IEEE) 1394, fiberchannel, Small Computer Systems Interface (SCSI), Universal Serial Bus(USB), and/or the like.

Network interfaces 1810 may accept, communicate, and/or connect to acommunications network 1813. Through a communications network 1813, theDCM-Platform controller is accessible through remote clients 1833 b(e.g., computers with web browsers) by users 1833 a. Network interfacesmay employ connection protocols such as, but not limited to: directconnect, Ethernet (thick, thin, twisted pair 10/100/1000 Base T, and/orthe like), Token Ring, wireless connection such as IEEE 802.11a-x,and/or the like. Should processing requirements dictate a greater amountspeed and/or capacity, distributed network controllers (e.g.,Distributed DCM-Platform), architectures may similarly be employed topool, load balance, and/or otherwise increase the communicativebandwidth required by the DCM-Platform controller. A communicationsnetwork may be any one and/or the combination of the following: a directinterconnection; the Internet; a Local Area Network (LAN); aMetropolitan Area Network (MAN); an Operating Missions as Nodes on theInternet (OMNI); a secured custom connection; a Wide Area Network (WAN);a wireless network (e.g., employing protocols such as, but not limitedto a Wireless Application Protocol (WAP), I-mode, and/or the like);and/or the like. A network interface may be regarded as a specializedform of an input output interface. Further, multiple network interfaces1810 may be used to engage with various communications network types1813. For example, multiple network interfaces may be employed to allowfor the communication over broadcast, multicast, and/or unicastnetworks.

Input Output interfaces (I/O) 1808 may accept, communicate, and/orconnect to user input devices 1811, peripheral devices 1812,cryptographic processor devices 1828, and/or the like. I/O may employconnection protocols such as, but not limited to: audio: analog,digital, monaural, RCA, stereo, and/or the like; data: Apple Desktop Bus(ADB), IEEE 1394a-b, serial, universal serial bus (USB); infrared;joystick; keyboard; midi; optical; PC AT; PS/2; parallel; radio; videointerface: Apple Desktop Connector (ADC), BNC, coaxial, component,composite, digital, Digital Visual Interface (DVI), high-definitionmultimedia interface (HDMI), RCA, RF antennae, S-Video, VGA, and/or thelike; wireless transceivers: 802.11a/b/g/n/x; Bluetooth; cellular (e.g.,code division multiple access (CDMA), high speed packet access(HSPA(+)), high-speed downlink packet access (HSDPA), global system formobile communications (GSM), long term evolution (LTE), WiMax, etc.);and/or the like. One typical output device may include a video display,which typically comprises a Cathode Ray Tube (CRT) or Liquid CrystalDisplay (LCD) based monitor with an interface (e.g., DVI circuitry andcable) that accepts signals from a video interface, may be used. Thevideo interface composites information generated by a computersystemization and generates video signals based on the compositedinformation in a video memory frame. Another output device is atelevision set, which accepts signals from a video interface. Typically,the video interface provides the composited video information through avideo connection interface that accepts a video display interface (e.g.,an RCA composite video connector accepting an RCA composite video cable;a DVI connector accepting a DVI display cable, etc.).

User input devices 1811 often are a type of peripheral device 512 (seebelow) and may include: card readers, dongles, finger print readers,gloves, graphics tablets, joysticks, keyboards, microphones, mouse(mice), remote controls, retina readers, touch screens (e.g.,capacitive, resistive, etc.), trackballs, trackpads, sensors (e.g.,accelerometers, ambient light, GPS, gyroscopes, proximity, etc.),styluses, and/or the like.

Peripheral devices 1812 may be connected and/or communicate to I/Oand/or other facilities of the like such as network interfaces, storageinterfaces, directly to the interface bus, system bus, the CPU, and/orthe like. Peripheral devices may be external, internal and/or part ofthe DCM-Platform controller. Peripheral devices may include: antenna,audio devices (e.g., line-in, line-out, microphone input, speakers,etc.), cameras (e.g., still, video, webcam, etc.), dongles (e.g., forcopy protection, ensuring secure transactions with a digital signature,and/or the like), external processors (for added capabilities; e.g.,crypto devices 528), force-feedback devices (e.g., vibrating motors),network interfaces, printers, scanners, storage devices, transceivers(e.g., cellular, GPS, etc.), video devices (e.g., goggles, monitors,etc.), video sources, visors, and/or the like. Peripheral devices ofteninclude types of input devices (e.g., cameras).

It should be noted that although user input devices and peripheraldevices may be employed, the DCM-Platform controller may be embodied asan embedded, dedicated, and/or monitor-less (i.e., headless) device,wherein access would be provided over a network interface connection.

Cryptographic units such as, but not limited to, microcontrollers,processors 1826, interfaces 1827, and/or devices 1828 may be attached,and/or communicate with the DCM-Platform controller. A MC68HC16microcontroller, manufactured by Motorola Inc., may be used for and/orwithin cryptographic units. The MC68HC16 microcontroller utilizes a16-bit multiply-and-accumulate instruction in the 16 MHz configurationand requires less than one second to perform a 512-bit RSA private keyoperation. Cryptographic units support the authentication ofcommunications from interacting agents, as well as allowing foranonymous transactions. Cryptographic units may also be configured aspart of the CPU. Equivalent microcontrollers and/or processors may alsobe used. Other commercially available specialized cryptographicprocessors include: Broadcom's CryptoNetX and other Security Processors;nCipher's nShield; SafeNet's Luna PCI (e.g., 7100) series; SemaphoreCommunications' 40 MHz Roadrunner 184; Sun's Cryptographic Accelerators(e.g., Accelerator 6000 PCIe Board, Accelerator 500 Daughtercard); ViaNano Processor (e.g., L2100, L2200, U2400) line, which is capable ofperforming 500+16 MB/s of cryptographic instructions; VLSI Technology's33 MHz 6868; and/or the like.

Memory

Generally, any mechanization and/or embodiment allowing a processor toaffect the storage and/or retrieval of information is regarded as memory1829. However, memory is a fungible technology and resource, thus, anynumber of memory embodiments may be employed in lieu of or in concertwith one another. It is to be understood that the DCM-Platformcontroller and/or a computer systemization may employ various forms ofmemory 1829. For example, a computer systemization may be configuredwherein the operation of on-chip CPU memory (e.g., registers), RAM, ROM,and any other storage devices are provided by a paper punch tape orpaper punch card mechanism; however, such an embodiment would result inan extremely slow rate of operation. In a typical configuration, memory1829 will include ROM 18 o 6, RAM 1805, and a storage device 1814. Astorage device 1814 may be any conventional computer system storage.Storage devices may include a drum; a (fixed and/or removable) magneticdisk drive; a magneto-optical drive; an optical drive (i.e., Blueray, CDROM/RAM/Recordable (R)/ReWritable (RW), DVD R/RW, HD DVD R/RW etc.); anarray of devices (e.g., Redundant Array of Independent Disks (RAID));solid state memory devices (USB memory, solid state drives (SSD), etc.);other processor-readable storage mediums; and/or other devices of thelike. Thus, a computer systemization generally requires and makes use ofmemory.

Component Collection

The memory 1829 may contain a collection of program and/or databasecomponents and/or data such as, but not limited to: operating systemcomponent(s) 1815 (operating system); information server component(s)1816 (information server); user interface component(s) 1817 (userinterface); Web browser component(s) 1818 (Web browser); database(s)1819; mail server component(s) 1821; mail client component(s) 1822;cryptographic server component(s) 1820 (cryptographic server); theDCM-Platform component(s) 1835; and/or the like (i.e., collectively acomponent collection). These components may be stored and accessed fromthe storage devices and/or from storage devices accessible through aninterface bus. Although non-conventional program components such asthose in the component collection, typically, are stored in a localstorage device 1814, they may also be loaded and/or stored in memorysuch as: peripheral devices, RAM, remote storage facilities through acommunications network, ROM, various forms of memory, and/or the like.

Operating System

The operating system component 1815 is an executable program componentfacilitating the operation of the DCM-Platform controller. Typically,the operating system facilitates access of I/O, network interfaces,peripheral devices, storage devices, and/or the like. The operatingsystem may be a highly fault tolerant, scalable, and secure system suchas: Apple Macintosh OS X (Server); AT&T Plan 9; Be OS; Unix andUnix-like system distributions (such as AT&T's UNIX; Berkley SoftwareDistribution (BSD) variations such as FreeBSD, NetBSD, OpenBSD, and/orthe like; Linux distributions such as Red Hat, Ubuntu, and/or the like);and/or the like operating systems. However, more limited and/or lesssecure operating systems also may be employed such as Apple MacintoshOS, IBM OS/2, Microsoft DOS, Microsoft Windows2000/2003/3.1/95/98/CE/Millenium/NT/Vista/XP (Server), Palm OS, and/orthe like. An operating system may communicate to and/or with othercomponents in a component collection, including itself, and/or the like.Most frequently, the operating system communicates with other programcomponents, user interfaces, and/or the like. For example, the operatingsystem may contain, communicate, generate, obtain, and/or provideprogram component, system, user, and/or data communications, requests,and/or responses. The operating system, once executed by the CPU, mayenable the interaction with communications networks, data, I/O,peripheral devices, program components, memory, user input devices,and/or the like. The operating system may provide communicationsprotocols that allow the DCM-Platform controller to communicate withother entities through a communications network 1813. Variouscommunication protocols may be used by the DCM-Platform controller as asubcarrier transport mechanism for interaction, such as, but not limitedto: multicast, TCP/IP, UDP, unicast, and/or the like.

Information Server

An information server component 1816 is a stored program component thatis executed by a CPU. The information server may be a conventionalInternet information server such as, but not limited to Apache SoftwareFoundation's Apache, Microsoft's Internet Information Server, and/or thelike. The information server may allow for the execution of programcomponents through facilities such as Active Server Page (ASP), ActiveX,(ANSI) (Objective-) C (++), C# and/or .NET, Common Gateway Interface(CGI) scripts, dynamic (D) hypertext markup language (HTML), FLASH,Java, JavaScript, Practical Extraction Report Language (PERL), HypertextPre-Processor (PHP), pipes, Python, wireless application protocol (WAP),WebObjects, and/or the like. The information server may support securecommunications protocols such as, but not limited to, File TransferProtocol (FTP); HyperText Transfer Protocol (HTTP); Secure HypertextTransfer Protocol (HTTPS), Secure Socket Layer (SSL), messagingprotocols (e.g., America Online (AOL) Instant Messenger (AIM),Application Exchange (APEX), ICQ, Internet Relay Chat (IRC), MicrosoftNetwork (MSN) Messenger Service, Presence and Instant Messaging Protocol(PRIM), Internet Engineering Task Force's (IETF's) Session InitiationProtocol (SIP), SIP for Instant Messaging and Presence LeveragingExtensions (SIMPLE), open XML-based Extensible Messaging and PresenceProtocol (XMPP) (i.e., Jabber or Open Mobile Alliance's (OMA's) InstantMessaging and Presence Service (IMPS)), Yahoo!Instant Messenger Service,and/or the like. The information server provides results in the form ofWeb pages to Web browsers, and allows for the manipulated generation ofthe Web pages through interaction with other program components. After aDomain Name System (DNS) resolution portion of an HTTP request isresolved to a particular information server, the information serverresolves requests for information at specified locations on theDCM-Platform controller based on the remainder of the HTTP request. Forexample, a request such as http://123.124.125.126/myInformation.htmlmight have the IP portion of the request “123.124.125.126” resolved by aDNS server to an information server at that IP address; that informationserver might in turn further parse the http request for the“/myInformation.html” portion of the request and resolve it to alocation in memory containing the information “myInformation.html.”Additionally, other information serving protocols may be employed acrossvarious ports, e.g., FTP communications across port 21, and/or the like.An information server may communicate to and/or with other components ina component collection, including itself, and/or facilities of the like.Most frequently, the information server communicates with theDCM-Platform database 1819, operating systems, other program components,user interfaces, Web browsers, and/or the like.

Access to the DCM-Platform database may be achieved through a number ofdatabase bridge mechanisms such as through scripting languages asenumerated below (e.g., CGI) and through inter-application communicationchannels as enumerated below (e.g., CORBA, WebObjects, etc.). Any datarequests through a Web browser are parsed through the bridge mechanisminto appropriate grammars as required by the DCM-Platform. In oneembodiment, the information server would provide a Web form accessibleby a Web browser. Entries made into supplied fields in the Web form aretagged as having been entered into the particular fields, and parsed assuch. The entered terms are then passed along with the field tags, whichact to instruct the parser to generate queries directed to appropriatetables and/or fields. In one embodiment, the parser may generate queriesin standard SQL by instantiating a search string with the properjoin/select commands based on the tagged text entries, wherein theresulting command is provided over the bridge mechanism to theDCM-Platform as a query. Upon generating query results from the query,the results are passed over the bridge mechanism, and may be parsed forformatting and generation of a new results Web page by the bridgemechanism. Such a new results Web page is then provided to theinformation server, which may supply it to the requesting Web browser.

Also, an information server may contain, communicate, generate, obtain,and/or provide program component, system, user, and/or datacommunications, requests, and/or responses.

User Interface

Computer interfaces in some respects are similar to automobile operationinterfaces. Automobile operation interface elements such as steeringwheels, gearshifts, and speedometers facilitate the access, operation,and display of automobile resources, and status. Computer interactioninterface elements such as check boxes, cursors, menus, scrollers, andwindows (collectively and commonly referred to as widgets) similarlyfacilitate the access, capabilities, operation, and display of data andcomputer hardware and operating system resources, and status. Operationinterfaces are commonly called user interfaces. Graphical userinterfaces (GUIs) such as the Apple Macintosh Operating System's Aqua,IBM's OS/2, Microsoft's Windows2000/2003/3.1/95/98/CE/Millenium/NT/XP/Vista/7 (i.e., Aero), Unix'sX-Windows (e.g., which may include additional Unix graphic interfacelibraries and layers such as K Desktop Environment (KDE), mythTV and GNUNetwork Object Model Environment (GNOME)), web interface libraries(e.g., ActiveX, AJAX, (D)HTML, FLASH, Java, JavaScript, etc. interfacelibraries such as, but not limited to, Dojo, jQuery(UI), MooTools,Prototype, script.aculo.us, SWFObject, Yahoo!User Interface, any ofwhich may be used and) provide a baseline and means of accessing anddisplaying information graphically to users.

A user interface component 1817 is a stored program component that isexecuted by a CPU. The user interface may be a conventional graphic userinterface as provided by, with, and/or atop operating systems and/oroperating environments such as already discussed. The user interface mayallow for the display, execution, interaction, manipulation, and/oroperation of program components and/or system facilities through textualand/or graphical facilities. The user interface provides a facilitythrough which users may affect, interact, and/or operate a computersystem. A user interface may communicate to and/or with other componentsin a component collection, including itself, and/or facilities of thelike. Most frequently, the user interface communicates with operatingsystems, other program components, and/or the like. The user interfacemay contain, communicate, generate, obtain, and/or provide programcomponent, system, user, and/or data communications, requests, and/orresponses.

Web Browser

A Web browser component 1818 is a stored program component that isexecuted by a CPU. The Web browser may be a conventional hypertextviewing application such as Microsoft Internet Explorer or NetscapeNavigator. Secure Web browsing may be supplied with 128 bit (or greater)encryption by way of HTTPS, SSL, and/or the like. Web browsers allowingfor the execution of program components through facilities such asActiveX, AJAX, (D)HTML, FLASH, Java, JavaScript, web browser plug-inAPIs (e.g., FireFox, Safari Plug-in, and/or the like APIs), and/or thelike. Web browsers and like information access tools may be integratedinto PDAs, cellular telephones, and/or other mobile devices. A Webbrowser may communicate to and/or with other components in a componentcollection, including itself, and/or facilities of the like. Mostfrequently, the Web browser communicates with information servers,operating systems, integrated program components (e.g., plug-ins),and/or the like; e.g., it may contain, communicate, generate, obtain,and/or provide program component, system, user, and/or datacommunications, requests, and/or responses. Also, in place of a Webbrowser and information server, a combined application may be developedto perform similar operations of both. The combined application wouldsimilarly affect the obtaining and the provision of information tousers, user agents, and/or the like from the DCM-Platform enabled nodes.The combined application may be nugatory on systems employing standardWeb browsers.

Mail Server

A mail server component 1821 is a stored program component that isexecuted by a CPU 1803. The mail server may be a conventional Internetmail server such as, but not limited to sendmail, Microsoft Exchange,and/or the like. The mail server may allow for the execution of programcomponents through facilities such as ASP, ActiveX, (ANSI) (Objective-)C (++), C# and/or .NET, CGI scripts, Java, JavaScript, PERL, PHP, pipes,Python, WebObjects, and/or the like. The mail server may supportcommunications protocols such as, but not limited to: Internet messageaccess protocol (IMAP), Messaging Application Programming Interface(MAPI)/Microsoft Exchange, post office protocol (POP3), simple mailtransfer protocol (SMTP), and/or the like. The mail server can route,forward, and process incoming and outgoing mail messages that have beensent, relayed and/or otherwise traversing through and/or to theDCM-Platform.

Access to the DCM-Platform mail may be achieved through a number of APIsoffered by the individual Web server components and/or the operatingsystem.

Also, a mail server may contain, communicate, generate, obtain, and/orprovide program component, system, user, and/or data communications,requests, information, and/or responses.

Mail Client

A mail client component 1822 is a stored program component that isexecuted by a CPU 1803. The mail client may be a conventional mailviewing application such as Apple Mail, Microsoft Entourage, MicrosoftOutlook, Microsoft Outlook Express, Mozilla, Thunderbird, and/or thelike. Mail clients may support a number of transfer protocols, such as:IMAP, Microsoft Exchange, POP3, SMTP, and/or the like. A mail client maycommunicate to and/or with other components in a component collection,including itself, and/or facilities of the like. Most frequently, themail client communicates with mail servers, operating systems, othermail clients, and/or the like; e.g., it may contain, communicate,generate, obtain, and/or provide program component, system, user, and/ordata communications, requests, information, and/or responses. Generally,the mail client provides a facility to compose and transmit electronicmail messages.

Cryptographic Server

A cryptographic server component 1820 is a stored program component thatis executed by a CPU 1803, cryptographic processor 1826, cryptographicprocessor interface 1827, cryptographic processor device 1828, and/orthe like. Cryptographic processor interfaces will allow for expeditionof encryption and/or decryption requests by the cryptographic component;however, the cryptographic component, alternatively, may run on aconventional CPU. The cryptographic component allows for the encryptionand/or decryption of provided data. The cryptographic component allowsfor both symmetric and asymmetric (e.g., Pretty Good Protection (PGP))encryption and/or decryption. The cryptographic component may employcryptographic techniques such as, but not limited to: digitalcertificates (e.g., X.509 authentication framework), digital signatures,dual signatures, enveloping, password access protection, public keymanagement, and/or the like. The cryptographic component will facilitatenumerous (encryption and/or decryption) security protocols such as, butnot limited to: checksum, Data Encryption Standard (DES), EllipticalCurve Encryption (ECC), International Data Encryption Algorithm (IDEA),Message Digest 5 (MD5, which is a one way hash operation), passwords,Rivest Cipher (RC5), Rijndael, RSA (which is an Internet encryption andauthentication system that uses an algorithm developed in 1977 by RonRivest, Adi Shamir, and Leonard Adleman), Secure Hash Algorithm (SHA),Secure Socket Layer (SSL), Secure Hypertext Transfer Protocol (HTTPS),and/or the like. Employing such encryption security protocols, theDCM-Platform may encrypt all incoming and/or outgoing communications andmay serve as node within a virtual private network (VPN) with a widercommunications network. The cryptographic component facilitates theprocess of “security authorization” whereby access to a resource isinhibited by a security protocol wherein the cryptographic componenteffects authorized access to the secured resource. In addition, thecryptographic component may provide unique identifiers of content, e.g.,employing and MD5 hash to obtain a unique signature for an digital audiofile. A cryptographic component may communicate to and/or with othercomponents in a component collection, including itself, and/orfacilities of the like. The cryptographic component supports encryptionschemes allowing for the secure transmission of information across acommunications network to enable the DCM-Platform component to engage insecure transactions if so desired. The cryptographic componentfacilitates the secure accessing of resources on the DCM-Platform andfacilitates the access of secured resources on remote systems; i.e., itmay act as a client and/or server of secured resources. Most frequently,the cryptographic component communicates with information servers,operating systems, other program components, and/or the like. Thecryptographic component may contain, communicate, generate, obtain,and/or provide program component, system, user, and/or datacommunications, requests, and/or responses.

The DCM-Platform Database

The DCM-Platform database component 1819 may be embodied in a databaseand its stored data. The database is a stored program component, whichis executed by the CPU; the stored program component portion configuringthe CPU to process the stored data. The database may be a conventional,fault tolerant, relational, scalable, secure database such as Oracle orSybase. Relational databases are an extension of a flat file. Relationaldatabases consist of a series of related tables. The tables areinterconnected via a key field. Use of the key field allows thecombination of the tables by indexing against the key field; i.e., thekey fields act as dimensional pivot points for combining informationfrom various tables. Relationships generally identify links maintainedbetween tables by matching primary keys. Primary keys represent fieldsthat uniquely identify the rows of a table in a relational database.More precisely, they uniquely identify rows of a table on the “one” sideof a one-to-many relationship.

Alternatively, the DCM-Platform database may be implemented usingvarious standard data-structures, such as an array, hash, (linked) list,struct, structured text file (e.g., XML), table, and/or the like. Suchdata-structures may be stored in memory and/or in (structured) files. Inanother alternative, an object-oriented database may be used, such asFrontier, ObjectStore, Poet, Zope, and/or the like. Object databases caninclude a number of object collections that are grouped and/or linkedtogether by common attributes; they may be related to other objectcollections by some common attributes. Object-oriented databases performsimilarly to relational databases with the exception that objects arenot just pieces of data but may have other types of capabilitiesencapsulated within a given object. If the DCM-Platform database isimplemented as a data-structure, the use of the DCM-Platform database1819 may be integrated into another component such as the DCM-Platformcomponent 1835. Also, the database may be implemented as a mix of datastructures, objects, and relational structures. Databases may beconsolidated and/or distributed in countless variations through standarddata processing techniques. Portions of databases, e.g., tables, may beexported and/or imported and thus decentralized and/or integrated.

In one embodiment, the database component 519 includes several tables519 a-e. A User table 1819 a includes fields such as, but not limitedto: UserID, UserAddress, UserPhoneNumer, UserName, UserAddress,UserPassword, UserType, UserPreference, UserAccount, and/or the like.The User table may support and/or track multiple entity accounts on aDCM-Platform. A Hardware table 1819 b includes fields such as, but notlimited to: HardwareID, UserID, ScriptID, ConvAssetID, HardwareType,HardwareName, DataFormattingRequirements, HardwareProtocols,AddressInfo, UsageHistory, HardwareRequirements and/or the like. AConversation Asset table 1819 c includes fields such as, but not limitedto: AssetID, AssetSymbol, AssetName, AssetType, AIAgentID, AIAgentName,ExchangeID, PortfolioID, AssetIndex, AssetOwnership, AssetNegotiator,AssetWrapperTag, AssetSize, ScriptID and/or the like. An AI Agent table119 d includes fields such as, but not limited to: AgentID, AgentName,AssetID, AssetName, AssetOwnership, PortfolioID, AgentHistory,AgentCredit, and/or the like. A Portfolio table 1819 e includes fieldssuch as, but not limited to: PortfolioID, PortfolioName, AssetID,AssetName, PortfoioOwnership, PortfolioWrapperTag, PortfolioIndex,PortfolioNegatiator, AgentID, and/or the like. An Exchange table 1819 fincludes fields such as, but not limited to: ExchangeID, ExchangeParty,ExchangeIndex, ExchangeTime, AssetID, PortfolioID, AgentID, and/or thelike. A Scripts table 1819 g includes fields such as, but not limitedto: ScriptID, ScriptName, ScriptTime, ScriptFile, AssetID, AgentID,HardwareID, ScriptFormat, ScriptType, ScriptProgram, ScriptAuthor,and/or the like. An author table 1819 h includes fields such as, but notlimited to: AuthorName, AuthorID, AuthorScript, AuthorAI, AuthorType,AuthorConversationID, and/or the like. An owner table 1819 i includesfields such as, but not limited to: OwnerName, OwnerType, OwnerID,OwnerAssetID, OwnerAI, OwnerLegalInfo, and/or the like. A transactiontable 1819 j includes fields such as, but not limited to: TransactionID,TransactionParty, TransactionOwner, TransactionAI, TransactionAsset,TranctionTime, TransactionPrice, TransactionVolume, and/or the like. Aknowledge table 1819 k includes fields such as, but not limited to:KnowledgeID, KnowledgeSource, KnowledgeScriptID, KnowledgeSearchID,KnowledgeDistributorID, and/or the like. A client table 1819 l includesfields such as, but not limited to: ClientID, ClientName, ClientAd,ClientAI, ClientProject, and/or the like.

In one embodiment, the DCM-Platform database may interact with otherdatabase systems. For example, employing a distributed database system,queries and data access by search DCM-Platform component may treat thecombination of the DCM-Platform database, an integrated data securitylayer database as a single database entity.

In one embodiment, user programs may contain various user interfaceprimitives, which may serve to update the DCM-Platform. Also, variousaccounts may require custom database tables depending upon theenvironments and the types of clients the DCM-Platform may need toserve. It should be noted that any unique fields may be designated as akey field throughout. In an alternative embodiment, these tables havebeen decentralized into their own databases and their respectivedatabase controllers (i.e., individual database controllers for each ofthe above tables). Employing standard data processing techniques, onemay further distribute the databases over several computersystemizations and/or storage devices. Similarly, configurations of thedecentralized database controllers may be varied by consolidating and/ordistributing the various database components 1819 a-l. The DCM-Platformmay be configured to keep track of various settings, inputs, andparameters via database controllers.

The DCM-Platform database may communicate to and/or with othercomponents in a component collection, including itself, and/orfacilities of the like. Most frequently, the DCM-Platform databasecommunicates with the DCM-Platform component, other program components,and/or the like. The database may contain, retain, and provideinformation regarding other nodes and data.

The DCM-Platforms

The DCM-Platform component 1835 is a stored program component that isexecuted by a CPU. In one embodiment, the DCM-Platform componentincorporates any and/or all combinations of the aspects of theDCM-Platform that was discussed in the previous figures. As such, theDCM-Platform affects accessing, obtaining and the provision ofinformation, services, transactions, and/or the like across variouscommunications networks.

The DCM-Platform transforms digital dialogue from consumers, clientdemands and, Internet search inputs via DCM-Platform componentsConversation Monetizer 1845, Asset Generator 1844, Knowledge Builder1843, Social Media Synchronizer 1842 and Dialogue Generator 1841 intotradable digital assets, and client needs based artificial intelligencecampaign plan outputs.

The DCM-Platform component enabling access of information between nodesmay be developed by employing standard development tools and languagessuch as, but not limited to: Apache components, Assembly, ActiveX,binary executables, (ANSI) (Objective-) C (++), C# and/or .NET, databaseadapters, CGI scripts, Java, JavaScript, mapping tools, procedural andobject oriented development tools, PERL, PHP, Python, shell scripts, SQLcommands, web application server extensions, web developmentenvironments and libraries (e.g., Microsoft's ActiveX; Adobe AIR, FLEX &FLASH; AJAX; (D)HTML; Dojo, Java; JavaScript; jQuery(UI); MooTools;Prototype; script.aculo.us; Simple Object Access Protocol (SOAP);SWFObject; Yahoo!User Interface; and/or the like), WebObjects, and/orthe like. In one embodiment, the DCM-Platform server employs acryptographic server to encrypt and decrypt communications. TheDCM-Platform component may communicate to and/or with other componentsin a component collection, including itself, and/or facilities of thelike. Most frequently, the DCM-Platform component communicates with theDCM-Platform database, operating systems, other program components,and/or the like. The DCM-Platform may contain, communicate, generate,obtain, and/or provide program component, system, user, and/or datacommunications, requests, and/or responses.

Distributed DCM-Platforms

The structure and/or operation of any of the DCM-Platform nodecontroller components may be combined, consolidated, and/or distributedin any number of ways to facilitate development and/or deployment.Similarly, the component collection may be combined in any number ofways to facilitate deployment and/or development. To accomplish this,one may integrate the components into a common code base or in afacility that can dynamically load the components on demand in anintegrated fashion.

The component collection may be consolidated and/or distributed incountless variations through standard data processing and/or developmenttechniques. Multiple instances of any one of the program components inthe program component collection may be instantiated on a single node,and/or across numerous nodes to improve performance throughload-balancing and/or data-processing techniques. Furthermore, singleinstances may also be distributed across multiple controllers and/orstorage devices; e.g., databases. All program component instances andcontrollers working in concert may do so through standard dataprocessing communication techniques.

The configuration of the DCM-Platform controller will depend on thecontext of system deployment. Factors such as, but not limited to, thebudget, capacity, location, and/or use of the underlying hardwareresources may affect deployment requirements and configuration.Regardless of if the configuration results in more consolidated and/orintegrated program components, results in a more distributed series ofprogram components, and/or results in some combination between aconsolidated and distributed configuration, data may be communicated,obtained, and/or provided. Instances of components consolidated into acommon code base from the program component collection may communicate,obtain, and/or provide data. This may be accomplished throughintra-application data processing communication techniques such as, butnot limited to: data referencing (e.g., pointers), internal messaging,object instance variable communication, shared memory space, variablepassing, and/or the like.

If component collection components are discrete, separate, and/orexternal to one another, then communicating, obtaining, and/or providingdata with and/or to other component components may be accomplishedthrough inter-application data processing communication techniques suchas, but not limited to: Application Program Interfaces (API) informationpassage; (distributed) Component Object Model ((D)COM), (Distributed)Object Linking and Embedding ((D)OLE), and/or the like), Common ObjectRequest Broker Architecture (CORBA), Jini local and remote applicationprogram interfaces, JavaScript Object Notation (JSON), Remote MethodInvocation (RMI), SOAP, process pipes, shared files, and/or the like.Messages sent between discrete component components forinter-application communication or within memory spaces of a singularcomponent for intra-application communication may be facilitated throughthe creation and parsing of a grammar. A grammar may be developed byusing development tools such as lex, yacc, XML, and/or the like, whichallow for grammar generation and parsing capabilities, which in turn mayform the basis of communication messages within and between components.

For example, a grammar may be arranged to recognize the tokens of anHTTP post command, e.g.:

w3c -post http://... Value1

where Value1 is discerned as being a parameter because “http://” is partof the grammar syntax, and what follows is considered part of the postvalue. Similarly, with such a grammar, a variable “Value1” may beinserted into an “http://” post command and then sent. The grammarsyntax itself may be presented as structured data that is interpretedand/or otherwise used to generate the parsing mechanism (e.g., a syntaxdescription text file as processed by lex, yacc, etc.). Also, once theparsing mechanism is generated and/or instantiated, it itself mayprocess and/or parse structured data such as, but not limited to:character (e.g., tab) delineated text, HTML, structured text streams,XML, and/or the like structured data. In another embodiment,inter-application data processing protocols themselves may haveintegrated and/or readily available parsers (e.g., JSON, SOAP, and/orlike parsers) that may be employed to parse (e.g., communications) data.Further, the parsing grammar may be used beyond message parsing, but mayalso be used to parse: databases, data collections, data stores,structured data, and/or the like. Again, the desired configuration willdepend upon the context, environment, and requirements of systemdeployment.

For example, in some implementations, the DCM-Platform controller may beexecuting a PHP script implementing a Secure Sockets Layer (“SSL”)socket server via the information sherver, which listens to incomingcommunications on a server port to which a client may send data, e.g.,data encoded in JSON format. Upon identifying an incoming communication,the PHP script may read the incoming message from the client device,parse the received JSON-encoded text data to extract information fromthe JSON-encoded text data into PHP script variables, and store the data(e.g., client identifying information, etc.) and/or extractedinformation in a relational database accessible using the StructuredQuery Language (“SQL”). An exemplary listing, written substantially inthe form of PHP/SQL commands, to accept JSON-encoded input data from aclient device via a SSL connection, parse the data to extract variables,and store the data to a database, is provided below:

<?PHP header(‘Content-Type: text/plain’); // set ip address and port tolisten to for incoming data $address = ‘192.168.0.100’; $port = 255; //create a server-side SSL socket, listen for/accept incomingcommunication $sock = socket_create(AF_INET, SOCK_STREAM, 0);socket_bind($sock, $address, $port) or die(‘Could not bind to address’);socket_listen($sock); $client = socket_accept($sock); // read input datafrom client device in 1024 byte blocks until end of message do {    $input = “”;     $input = socket_read($client, 1024);     $data . =$input; } while($input != “”); // parse data to extract variables $obj =json_decode($data, true); // store input data in a databasemysql_connect(″201.408.185.132″,$DBserver,$password); // access databaseserver mysql_select(″CLIENT_DB.SQL″); // select database to appendmysql_query(“INSERT INTO UserTable (transmission) VALUES ($data)”); //add data to UserTable table in a CLIENT databasemysql_close(″CLIENT_DB.SQL″); // close connection to database ?>

Also, the following resources may be used to provide example embodimentsregarding SOAP parser implementation:

http://www.xav.com/perl/site/lib/SOAP/Parser.htmlhttp://publib.boulder.ibm.com/infocenter/tivihelp/v2r1/index.jsp?topic=/com.ibm.IBMDI.doc/referenceguide295.htm

and other parser implementations:

http://publib.boulder.ibm.com/infocenter/tivihelp/v2r1/index.jsp?topic=/com.ibm.IBMDI.doc/referenceguide259.htm

all of which are hereby expressly incorporated by reference.

Additional embodiments of the DCM-Platform may comprise the following:

1. A digital conversation generating processor-implemented methodembodiment, comprising:

instantiating a conversational artificial-intelligence agent;

identifying an individual target for conversation;

initiating a conversation with the individual target by theartificial-intelligence agent by providing a first portion of aconversational dialogue to the individual target;

recording a response from the individual target to the first portion ofthe conversational dialogue; and

responding to the response from the individual target with a nextcontextual portion of the conversational dialogue.

2. The method of embodiment 1, further comprising:

receiving an advertising client request; and

creating a dialogue agent based on the client request.

3. The method of embodiment 2, further comprising:

populating the dialogue agent on social media; and

implement the dialogue agent to capture interactive dialogue actions.

4. The method of embodiment 2, wherein the creating the dialogue agentcomprises:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

5. The method of embodiment 4, wherein the completing dialogue agentapplication further comprises dialogue cloud with key words for searchengines;

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

6. The method of embodiment 1, wherein the artificial-intelligence agentis an avatar on a social media platform.

7. The method of embodiment 1, further comprising:

registering the conversation on a virtual asset exchange platform.

8. The method of embodiment 1, further comprising:

registering the conversation on a financial trading platform.

9. The method of embodiment 1, further comprising:

providing options for a conditional logic.

10. The method of embodiment 1, further comprising:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

11. The method of embodiment 10, wherein the search comprises a key wordbased Google search.

12. The method of embodiment 11, further comprising:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

13. The method of embodiment 1, further comprising:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

14. The method of embodiment 1, further comprising:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

15. The method of embodiment 14, wherein the dialogue parameterscomprises a number of dialogue actions in the dialogue pathway and anamount of time take for each dialogue action.

16. The method of embodiment 15, further comprising aggregating dialoguepathways from a plurality of individual targets.

17. The method of embodiment 15, further comprising determining a dollarvalue associated with each dialogue action.

18. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

instantiate a conversational artificial-intelligence agent;

identify an individual target for conversation;

initiate a conversation with the individual target by theartificial-intelligence agent by providing a first portion of aconversational dialogue to the individual target;

record a response from the individual target to the first portion of theconversational dialogue; and

respond to the response from the individual target with a nextcontextual portion of the conversational dialogue.

19. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

receiving an advertising client request; and

creating a dialogue agent based on the client request.

20. The apparatus of embodiment 19, wherein the processor further issuesinstructions for:

populating the dialogue agent on social media; and

implement the dialogue agent to capture interactive dialogue actions.

21. The apparatus of embodiment 19, wherein the creating the dialogueagent comprises:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

22. The apparatus of embodiment 21, wherein the completing dialogueagent application further comprises dialogue cloud with key words forsearch engines;

populating on a social media platform;

generating links accessible from Internet and smart phone applications;

and

updating wrapper description identifications.

23. The apparatus of embodiment 18, wherein the artificial-intelligenceagent is an avatar on a social media platform.

24. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

registering the conversation on a virtual asset exchange platform.

25. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

registering the conversation on a financial trading platform.

26. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

providing options for a conditional logic.

27. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

28. The apparatus of embodiment 27, wherein the search comprises a keyword based Google search.

29. The apparatus of embodiment 28, wherein the processor further issuesinstructions for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

30. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

31. The apparatus of embodiment 18, wherein the processor further issuesinstructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

32. The apparatus of embodiment 31, wherein the dialogue parameterscomprises a number of dialogue actions in the dialogue pathway and anamount of time take for each dialogue action.

33. The apparatus of embodiment 32, wherein the processor further issuesinstructions for aggregating dialogue pathways from a plurality ofindividual targets.

34. The apparatus of embodiment 32, wherein the processor further issuesinstructions for determining a dollar value associated with eachdialogue action.

35. A digital conversation generating system embodiment, comprising:

means to instantiate a conversational artificial-intelligence agent;

means to identify an individual target for conversation;

means to initiate a conversation with the individual target by theartificial-intelligence agent by providing a first portion of aconversational dialogue to the individual target;

means to record a response from the individual target to the firstportion of the conversational dialogue; and

means to respond to the response from the individual target with a nextcontextual portion of the conversational dialogue.

36. The system of embodiment 35, further comprising means for:

receiving an advertising client request; and

creating a dialogue agent based on the client request.

37. The system of embodiment 36, further comprising means for:

populating the dialogue agent on social media; and

implement the dialogue agent to capture interactive dialogue actions.

38. The system of embodiment 36, wherein the creating the dialogue agentcomprises:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

39. The system of embodiment 38, wherein the completing dialogue agentapplication further comprises dialogue cloud with key words for searchengines;

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

40. The system of embodiment 35, wherein the artificial-intelligenceagent is an avatar on a social media platform.

41. The system of embodiment 35, further comprising means for:

registering the conversation on a virtual asset exchange platform.

42. The system of embodiment 35, further comprising means for:

registering the conversation on a financial trading platform.

43. The system of embodiment 35, further comprising means for:

providing options for a conditional logic.

44. The system of embodiment 35, further comprising means for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

45. The system of embodiment 44, wherein the search comprises a key wordbased Google search.

46. The system of embodiment 45, further comprising means for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

47. The system of embodiment 35, further comprising means for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

48. The system of embodiment 35, further comprising means for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

49. The system of embodiment 48, wherein the dialogue parameterscomprises a number of dialogue actions in the dialogue pathway and anamount of time take for each dialogue action.

50. The system of embodiment 49, further comprising means foraggregating dialogue pathways from a plurality of individual targets.

51. The system of embodiment 49, further comprising means fordetermining a dollar value associated with each dialogue action.

52. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

instantiate a conversational artificial-intelligence agent;

identify an individual target for conversation;

initiate a conversation with the individual target by theartificial-intelligence agent by providing a first portion of aconversational dialogue to the individual target;

record a response from the individual target to the first portion of theconversational dialogue; and

respond to the response from the individual target with a nextcontextual portion of the conversational dialogue.

53. The medium of embodiment 52, further storing processor-issueableinstructions for:

receiving an advertising client request; and

creating a dialogue agent based on the client request.

54. The medium of embodiment 53, further storing processor-issueableinstructions for:

populating the dialogue agent on social media; and

implement the dialogue agent to capture interactive dialogue actions.

55. The medium of embodiment 53, wherein the creating the dialogue agentcomprises:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

56. The medium of embodiment 55, wherein the completing dialogue agentapplication further comprises dialogue cloud with key words for searchengines;

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

57. The medium of embodiment 52, wherein the artificial-intelligenceagent is an avatar on a social media platform.

58. The medium of embodiment 52, further storing processor-issueableinstructions for:

registering the conversation on a virtual asset exchange platform.

59. The medium of embodiment 52, further storing processor-issueableinstructions for:

registering the conversation on a financial trading platform.

60. The medium of embodiment 52, further storing processor-issueableinstructions for:

providing options for a conditional logic.

61. The medium of embodiment 52, further storing processor-issueableinstructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

62. The medium of embodiment 61, wherein the search comprises a key wordbased Google search.

63. The medium of embodiment 62, further storing processor-issueableinstructions for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

64. The medium of embodiment 52, further storing processor-issueableinstructions for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

65. The medium of embodiment 52, further storing processor-issueableinstructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

66. The medium of embodiment 65, wherein the dialogue parameterscomprises a number of dialogue actions in the dialogue pathway and anamount of time take for each dialogue action.

67. The medium of embodiment 66, further storing processor-issueableinstructions for aggregating dialogue pathways from a plurality ofindividual targets.

68. The medium of embodiment 66, further storing processor-issueableinstructions for determining a dollar value associated with eachdialogue action.

69. A digital conversation value exchange processor-implemented methodembodiment, comprising:

receiving information indicating a demand for a digital conversationasset;

determining a type of the demanded digital conversation asset;

initializing an exchange procedure for the determined type of thedemanded digital conversation asset;

obtaining information required by the exchange procedure for thedetermined type of the demanded digital conversation asset; and

determining an index of the demanded digital conversation asset at leastbased on the obtained information for the determined type of thedemanded digital conversation asset.

70. The method of embodiment 69, further, comprising:

providing a payment to a provider of the conversationalartificial-intelligence agent for each response to each portion of theconversational dialogue.

71. The method of embodiment 70, wherein each successive responsewarrants an increased payment.

72. The method of embodiment 71, wherein a last response to theconversational dialogue resulting in a purchase warrants a furtherincreased payment.

73. The method of embodiment 72, wherein the further increased paymentis a percentage of the purchases.

74. The method of embodiment 73, wherein the response performance of theartificial-intelligence agent is recorded over multiple conversationaldialogues with multiple individuals.

75. The method of embodiment 74, wherein response performance of theartificial-intelligence agent may be compared to the performance ofother artificial-intelligence agents.

76. The method of embodiment 75, wherein artificial-intelligence agentsmay be traded on an exchange based on their performance.

77. The method of embodiment 76, wherein recorded responses andconversational dialogues across the artificial-intelligence may be minedfor trend information.

78. The method of embodiment 69, wherein the type of digitalconversation asset comprises at least one of:

conversation asset, conversation artificial intelligence entity asset,portfolio asset, exchange asset.

79. The method of embodiment 69, further comprising determining an assetnegotiator to negotiate a transaction between an asset owner and aninvestor.

80. The method of embodiment 69, further comprising: generating an assetwrapper for the demanded digital conversation asset.

81. The method of embodiment 70, wherein the asset wrapper identifies anasset owner, an asset author, an asset negotiator for the digitalconversation asset.

82. The method of embodiment 69, wherein the exchange procedurecomprises:

monetizing the digital conversation asset by determining shares of stockand price of a share;

determining cost factors; and

determining a dividends payment structure.

83. The method of embodiment 82, further comprising:

receiving trading information from a financial trading platform relatedto the demanded digital conversation asset; and

adjust the index of the demanded digital conversation asset based on thereceived trading information.

84. The method of embodiment 82, further comprising:

facilitating transfer of stock shares.

85. The method of embodiment 82, further comprising:

obtaining corporate certificate and credentials from an investor; and

assigning intellectual property rights to the investor.

86. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

receive information indicating a demand for a digital conversationasset;

determine a type of the demanded digital conversation asset;

initialize an exchange procedure for the determined type of the demandeddigital conversation asset;

obtain information required by the exchange procedure for the determinedtype of the demanded digital conversation asset; and

determine an index of the demanded digital conversation asset at leastbased on the obtained information for the determined type of thedemanded digital conversation asset.

87. The apparatus of embodiment 86, further, comprising:

providing a payment to a provider of the conversationalartificial-intelligence agent for each response to each portion of theconversational dialogue.

88. The apparatus of embodiment 87, wherein each successive responsewarrants an increased payment.

89. The apparatus of embodiment 88, wherein a last response to theconversational dialogue resulting in a purchase warrants a furtherincreased payment.

90. The apparatus of embodiment 89, wherein the further increasedpayment is a percentage of the purchases.

91. The apparatus of embodiment 90, wherein the response performance ofthe artificial-intelligence agent is recorded over multipleconversational dialogues with multiple individuals.

92. The apparatus of embodiment 91, wherein response performance of theartificial-intelligence agent may be compared to the performance ofother artificial-intelligence agents.

93. The apparatus of embodiment 92, wherein artificial-intelligenceagents may be traded on an exchange based on their performance.

94. The apparatus of embodiment 93, wherein recorded responses andconversational dialogues across the artificial-intelligence may be minedfor trend information.

95. The apparatus of embodiment 86, wherein the type of digitalconversation asset comprises at least one of:

conversation asset, conversation artificial intelligence entity asset,portfolio asset, exchange asset.

96. The apparatus of embodiment 86, wherein the processor further issuesinstructions for determining an asset negotiator to negotiate atransaction between an asset owner and an investor.

97. The apparatus of embodiment 86, wherein the processor further issuesinstructions for: generating an asset wrapper for the demanded digitalconversation asset.

98. The apparatus of embodiment 87, wherein the asset wrapper identifiesan asset owner, an asset author, an asset negotiator for the digitalconversation asset.

99. The apparatus of embodiment 86, wherein the exchange procedurecomprises:

monetizing the digital conversation asset by determining shares of stockand price of a share;

determining cost factors; and

determining a dividends payment structure.

100. The apparatus of embodiment 99, wherein the processor furtherissues instructions for:

receiving trading information from a financial trading platform relatedto the demanded digital conversation asset; and

adjust the index of the demanded digital conversation asset based on thereceived trading information.

101. The apparatus of embodiment 99, wherein the processor furtherissues instructions for:

facilitating transfer of stock shares.

102. The apparatus of embodiment 99, wherein the processor furtherissues instructions for:

obtaining corporate certificate and credentials from an investor; and

assigning intellectual property rights to the investor.

103. A digital conversation generating system embodiment, comprising:

means to receive information indicating a demand for a digitalconversation asset;

means to determine a type of the demanded digital conversation asset;

means to initialize an exchange procedure for the determined type of thedemanded digital conversation asset;

means to obtain information required by the exchange procedure for thedetermined type of the demanded digital conversation asset; and

means to determine an index of the demanded digital conversation assetat least based on the obtained information for the determined type ofthe demanded digital conversation asset.

104. The system of embodiment 103, further, comprising:

providing a payment to a provider of the conversationalartificial-intelligence agent for each response to each portion of theconversational dialogue.

105. The system of embodiment 104, wherein each successive responsewarrants an increased payment.

106. The system of embodiment 105, wherein a last response to theconversational dialogue resulting in a purchase warrants a furtherincreased payment.

107. The system of embodiment 106, wherein the further increased paymentis a percentage of the purchases.

108. The system of embodiment 107, wherein the response performance ofthe artificial-intelligence agent is recorded over multipleconversational dialogues with multiple individuals.

109. The system of embodiment 108, wherein response performance of theartificial-intelligence agent may be compared to the performance ofother artificial-intelligence agents.

110. The system of embodiment 109, wherein artificial-intelligenceagents may be traded on an exchange based on their performance.

111. The system of embodiment 110, wherein recorded responses andconversational dialogues across the artificial-intelligence may be minedfor trend information.

112. The system of embodiment 103, wherein the type of digitalconversation asset comprises at least one of:

conversation asset, conversation artificial intelligence entity asset,portfolio asset, exchange asset.

113. The system of embodiment 103, further comprising means fordetermining an asset negotiator to negotiate a transaction between anasset owner and an investor.

114. The system of embodiment 103, further comprising means for:generating an asset wrapper for the demanded digital conversation asset.

115. The system of embodiment 104, wherein the asset wrapper identifiesan asset owner, an asset author, an asset negotiator for the digitalconversation asset.

116. The system of embodiment 103, wherein the exchange procedurecomprises:

monetizing the digital conversation asset by determining shares of stockand price of a share;

determining cost factors; and

determining a dividends payment structure.

117. The system of embodiment 116, further comprising means for:

receiving trading information from a financial trading platform relatedto the demanded digital conversation asset; and

adjust the index of the demanded digital conversation asset based on thereceived trading information.

118. The system of embodiment 116, further comprising means for:

facilitating transfer of stock shares.

119. The system of embodiment 116, further comprising means for:

obtaining corporate certificate and credentials from an investor; and

assigning intellectual property rights to the investor.

120. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

receive information indicating a demand for a digital conversationasset;

determine a type of the demanded digital conversation asset;

initialize an exchange procedure for the determined type of the demandeddigital conversation asset;

obtain information required by the exchange procedure for the determinedtype of the demanded digital conversation asset; and

determine an index of the demanded digital conversation asset at leastbased on the obtained information for the determined type of thedemanded digital conversation asset.

121. The medium of embodiment 120, further, comprising:

providing a payment to a provider of the conversationalartificial-intelligence agent for each response to each portion of theconversational dialogue.

122. The medium of embodiment 121, wherein each successive responsewarrants an increased payment.

123. The medium of embodiment 122, wherein a last response to theconversational dialogue resulting in a purchase warrants a furtherincreased payment.

124. The medium of embodiment 123, wherein the further increased paymentis a percentage of the purchases.

125. The medium of embodiment 124, wherein the response performance ofthe artificial-intelligence agent is recorded over multipleconversational dialogues with multiple individuals.

126. The medium of embodiment 125, wherein response performance of theartificial-intelligence agent may be compared to the performance ofother artificial-intelligence agents.

127. The medium of embodiment 126, wherein artificial-intelligenceagents may be traded on an exchange based on their performance.

128. The medium of embodiment 127, wherein recorded responses andconversational dialogues across the artificial-intelligence may be minedfor trend information.

129. The medium of embodiment 120, wherein the type of digitalconversation asset comprises at least one of:

conversation asset, conversation artificial intelligence entity asset,portfolio asset, exchange asset.

130. The medium of embodiment 120, further storing processor-issuableinstructions for determining an asset negotiator to negotiate atransaction between an asset owner and an investor.

131. The medium of embodiment 120, further storing processor-issuableinstructions for: generating an asset wrapper for the demanded digitalconversation asset.

132. The medium of embodiment 121, wherein the asset wrapper identifiesan asset owner, an asset author, an asset negotiator for the digitalconversation asset.

133. The medium of embodiment 120, wherein the exchange procedurecomprises:

monetizing the digital conversation asset by determining shares of stockand price of a share;

determining cost factors; and

determining a dividends payment structure.

134. The medium of embodiment 133, further storing processor-issuableinstructions for:

receiving trading information from a financial trading platform relatedto the demanded digital conversation asset; and

adjust the index of the demanded digital conversation asset based on thereceived trading information.

135. The medium of embodiment 133, further storing processor-issuableinstructions for:

facilitating transfer of stock shares.

136. The medium of embodiment 133, further storing processor-issuableinstructions for:

obtaining corporate certificate and credentials from an investor; and

assigning intellectual property rights to the investor.

137. A digital conversation generating processor-implemented methodembodiment, comprising:

creating a dialogue agent application;

populating the created dialogue agent application on a dialogueplatform;

receiving a dialogue action from an individual target via the dialogueplatform;

generating a dialogue line in response to the received dialogue actionvia the dialogue agent application; and

recording an interactive dialogue comprising the dialogue action and thegenerated dialogue line.

138. The method of embodiment 137, wherein the dialogue platform is anautomatic dialing system.

139. The method of embodiment 137, wherein the dialogue platform is asocial media platform.

140. The method of embodiment 137, wherein the dialogue platform is amobile platform.

141. The method of embodiment 137, wherein creating the dialogue agentapplication further comprises:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

142. The method of embodiment 137, wherein the dialogue action comprisesan inquiry for information.

143. The method of embodiment 137, wherein the dialogue line comprises ahyperlink connected to a search engine.

144. The method of embodiment 137, wherein the dialogue line comprises ahyperlink connected to another dialogue agent application.

145. The method of embodiment 137, further comprising:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

146. The method of embodiment 137, further comprising:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

147. The method of embodiment 146, further comprising:

determining a conversation unit value of the interactive dialogue basedon the pathway.

148. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

create a dialogue agent application;

populate the created dialogue agent application on a dialogue platform;

receive a dialogue action from an individual target via the dialogueplatform;

generate a dialogue line in response to the received dialogue action viathe dialogue agent application; and

record an interactive dialogue comprising the dialogue action and thegenerated dialogue line.

149. The apparatus of embodiment 148, wherein the dialogue platform isan automatic dialing system.

150. The apparatus of embodiment 148, wherein the dialogue platform is asocial media platform.

151. The apparatus of embodiment 148, wherein the dialogue platform is amobile platform.

152. The apparatus of embodiment 148, wherein creating the dialogueagent application further comprises:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

153. The apparatus of embodiment 148, wherein the dialogue actioncomprises an inquiry for information.

154. The apparatus of embodiment 148, wherein the dialogue linecomprises a hyperlink connected to a search engine.

155. The apparatus of embodiment 148, wherein the dialogue linecomprises a hyperlink connected to another dialogue agent application.

156. The apparatus of embodiment 148, wherein the processor furtherissues instructions for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

157. The apparatus of embodiment 148, wherein the processor furtherissues instructions for:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

158. The apparatus of embodiment 157, wherein the processor furtherissues instructions for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

159. A digital conversation generating system embodiment, comprising:

means to create a dialogue agent application;

means to populate the created dialogue agent application on a dialogueplatform;

means to receive a dialogue action from an individual target via thedialogue platform;

means to generate a dialogue line in response to the received dialogueaction via the dialogue agent application; and

means to record an interactive dialogue comprising the dialogue actionand the generated dialogue line.

160. The system of embodiment 159, wherein the dialogue platform is anautomatic dialing system.

161. The system of embodiment 159, wherein the dialogue platform is asocial media platform.

162. The system of embodiment 159, wherein the dialogue platform is amobile platform.

163. The system of embodiment 159, wherein creating the dialogue agentapplication further comprises:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

164. The system of embodiment 159, wherein the dialogue action comprisesan inquiry for information.

165. The system of embodiment 159, wherein the dialogue line comprises ahyperlink connected to a search engine.

166. The system of embodiment 159, wherein the dialogue line comprises ahyperlink connected to another dialogue agent application.

167. The system of embodiment 159, further comprising means for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

168. The system of embodiment 159, further comprising means for:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

169. The system of embodiment 168, further comprising means for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

170. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

create a dialogue agent application;

populate the created dialogue agent application on a dialogue platform;

receive a dialogue action from an individual target via the dialogueplatform;

generate a dialogue line in response to the received dialogue action viathe dialogue agent application; and

record an interactive dialogue comprising the dialogue action and thegenerated dialogue line.

171. The medium of embodiment 170, wherein the dialogue platform is anautomatic dialing system.

172. The medium of embodiment 170, wherein the dialogue platform is asocial media platform.

173. The medium of embodiment 170, wherein the dialogue platform is amobile platform.

174. The medium of embodiment 170, wherein creating the dialogue agentapplication further comprises:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

175. The medium of embodiment 170, wherein the dialogue action comprisesan inquiry for information.

176. The medium of embodiment 170, wherein the dialogue line comprises ahyperlink connected to a search engine.

177. The medium of embodiment 170, wherein the dialogue line comprises ahyperlink connected to another dialogue agent application.

178. The medium of embodiment 170, further storing processor-issuableinstructions for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

179. The medium of embodiment 170, further storing processor-issuableinstructions for: determining a pathway of the recorded interactivedialogue; and

determining a plurality of parameters associated with the interactivedialogue.

180. The medium of embodiment 179, further storing processor-issuableinstructions for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

181. A digital conversation generating processor-implemented methodembodiment, comprising:

instantiating a dialogue platform on an individual device;

receiving a dialogue notice from a dialogue agent via the dialogueplatform;

submitting a dialogue action to the dialogue agent via the dialogueplatform; and

receiving a dialogue line in response to the submitted dialogue actionfrom the dialogue agent.

182. The method of embodiment 181, wherein the individual devicecomprises a computer.

183. The method of embodiment 181, wherein the individual deicecomprises a mobile smart phone.

184. The method of embodiment 181, wherein the dialogue platformcomprises a social media platform.

185. The method of embodiment 181, wherein the dialogue platformcomprises a smart phone application.

186. The method of embodiment 181, wherein the dialogue action isassociated with one condition in response to the dialogue notice.

187. The method of embodiment 181, wherein the received dialogue linecomprises a hyperlink connected to a search engine.

188. The method of embodiment 187, wherein the search engine is any ofGoogle, Yahoo, and Bing.

189. The method of embodiment 187, wherein the hyperlink comprises asearch based on key words included in the dialogue action.

190. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

instantiate a dialogue platform on an individual device;

receive a dialogue notice from a dialogue agent via the dialogueplatform;

submit a dialogue action to the dialogue agent via the dialogueplatform; and

receive a dialogue line in response to the submitted dialogue actionfrom the dialogue agent.

191. The apparatus of embodiment 190, wherein the individual devicecomprises a computer.

192. The apparatus of embodiment 190, wherein the individual deicecomprises a mobile smart phone.

193. The apparatus of embodiment 190, wherein the dialogue platformcomprises a social media platform.

194. The apparatus of embodiment 190, wherein the dialogue platformcomprises a smart phone application.

195. The apparatus of embodiment 190, wherein the dialogue action isassociated with one condition in response to the dialogue notice.

196. The apparatus of embodiment 190, wherein the received dialogue linecomprises a hyperlink connected to a search engine.

197. The apparatus of embodiment 196, wherein the search engine is anyof Google, Yahoo, and Bing.

198. The apparatus of embodiment 196, wherein the hyperlink comprises asearch based on key words included in the dialogue action.

199. A digital conversation generating system embodiment, comprising:

means to instantiate a dialogue platform on an individual device;

means to receive a dialogue notice from a dialogue agent via thedialogue platform;

means to submit a dialogue action to the dialogue agent via the dialogueplatform; and

means to receive a dialogue line in response to the submitted dialogueaction from the dialogue agent.

200. The system of embodiment 199, wherein the individual devicecomprises a computer.

201. The system of embodiment 199, wherein the individual deicecomprises a mobile smart phone.

202. The system of embodiment 199, wherein the dialogue platformcomprises a social media platform.

203. The system of embodiment 199, wherein the dialogue platformcomprises a smart phone application.

204. The system of embodiment 199, wherein the dialogue action isassociated with one condition in response to the dialogue notice.

205. The system of embodiment 199, wherein the received dialogue linecomprises a hyperlink connected to a search engine.

206. The system of embodiment 205, wherein the search engine is any ofGoogle, Yahoo, and Bing.

207. The system of embodiment 205, wherein the hyperlink comprises asearch based on key words included in the dialogue action.

208. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

instantiate a dialogue platform on an individual device;

receive a dialogue notice from a dialogue agent via the dialogueplatform;

submit a dialogue action to the dialogue agent via the dialogueplatform; and

receive a dialogue line in response to the submitted dialogue actionfrom the dialogue agent.

209. The medium of embodiment 208, wherein the individual devicecomprises a computer.

210. The medium of embodiment 208, wherein the individual deicecomprises a mobile smart phone.

211. The medium of embodiment 208, wherein the dialogue platformcomprises a social media platform.

212. The medium of embodiment 208, wherein the dialogue platformcomprises a smart phone application.

213. The medium of embodiment 208, wherein the dialogue action isassociated with one condition in response to the dialogue notice.

214. The medium of embodiment 208, wherein the received dialogue linecomprises a hyperlink connected to a search engine.

215. The medium of embodiment 214, wherein the search engine is any ofGoogle, Yahoo, and Bing.

216. The medium of embodiment 214, wherein the hyperlink comprises asearch based on key words included in the dialogue action.

217. A digital conversation management processor-implemented methodembodiment, comprising:

receiving a client request to purchase dialogue agent service;

determining a plurality of dialogue agent parameters based on the clientrequest;

creating a dialogue agent application;

populating the created dialogue agent application on a dialogueplatform; and

implementing the dialogue agent application on the dialogue platformwith an individual target.

218. The method of embodiment 217, wherein the client request comprisesa marketing campaign request.

219. The method of embodiment 217, wherein the dialogue agent servicecomprises a marketing plan.

220. The method of embodiment 217, wherein the plurality of dialogueagent parameters comprise a number of dialogue agents, and a selectionof a dialogue platform.

221. The method of embodiment 217, wherein the dialogue platformcomprises a social media platform.

222. The method of embodiment 217, further comprising:

devising a marketing plan; and

incorporating the devised marketing plan into the created dialogue agentapplication.

223. The method of embodiment 217, wherein the individual target is apotential consumer.

224. A digital conversation management apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

receive a client request to purchase dialogue agent service;

determine a plurality of dialogue agent parameters based on the clientrequest;

create a dialogue agent application;

populate the created dialogue agent application on a dialogue platform;and

implement the dialogue agent application on the dialogue platform withan individual target.

225. The apparatus of embodiment 224, wherein the client requestcomprises a marketing campaign request.

226. The apparatus of embodiment 224, wherein the dialogue agent servicecomprises a marketing plan.

227. The apparatus of embodiment 224, wherein the plurality of dialogueagent parameters comprise a number of dialogue agents, and a selectionof a dialogue platform.

228. The apparatus of embodiment 217, wherein the dialogue platformcomprises a social media platform.

229. The apparatus of embodiment 224, wherein the processor furtherissues instructions for:

devising a marketing plan; and

incorporating the devised marketing plan into the created dialogue agentapplication.

230. The apparatus of embodiment 224, wherein the individual target is apotential consumer.

231. A digital conversation management system embodiment, comprising:

means to receive a client request to purchase dialogue agent service;

means to determine a plurality of dialogue agent parameters based on theclient request;

means to create a dialogue agent application;

means to populate the created dialogue agent application on a dialogueplatform; and

means to implement the dialogue agent application on the dialogueplatform with an individual target.

232. The system of embodiment 231, wherein the client request comprisesa marketing campaign request.

233. The system of embodiment 231, wherein the dialogue agent servicecomprises a marketing plan.

234. The system of embodiment 231, wherein the plurality of dialogueagent parameters comprise a number of dialogue agents, and a selectionof a dialogue platform.

235. The system of embodiment 217, wherein the dialogue platformcomprises a social media platform.

236. The system of embodiment 231, further comprising:

devising a marketing plan; and

incorporating the devised marketing plan into the created dialogue agentapplication.

237. The system of embodiment 231, wherein the individual target is apotential consumer.

238. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

receive a client request to purchase dialogue agent service;

determine a plurality of dialogue agent parameters based on the clientrequest;

create a dialogue agent application;

populate the created dialogue agent application on a dialogue platform;and

implement the dialogue agent application on the dialogue platform withan individual target.

239. The medium of embodiment 238, wherein the client request comprisesa marketing campaign request.

240. The medium of embodiment 238, wherein the dialogue agent servicecomprises a marketing plan.

241. The medium of embodiment 238, wherein the plurality of dialogueagent parameters comprise a number of dialogue agents, and a selectionof a dialogue platform.

242. The medium of embodiment 217, wherein the dialogue platformcomprises a social media platform.

243. The medium of embodiment 238, further comprising:

devising a marketing plan; and

incorporating the devised marketing plan into the created dialogue agentapplication.

244. The medium of embodiment 238, wherein the individual target is apotential consumer.

245. A digital conversation exchange processor-implemented methodembodiment, comprising:

capturing an interactive dialogue between an individual target and adialogue agent;

creating a digital asset comprising at least the captured interactivedialogue;

instantiating the created digital asset;

generating a tradable financial instrument based on the instantiateddigital asset;

determining an index of the tradable financial instrument; and

facilitate a transaction of the financial instrument between an owner ofthe digital asset and an investor.

246. The method of embodiment 245, wherein the interactive dialogue issaved in a voice xml format.

247. The method of embodiment 245, wherein the individual targetcomprises a smart phone.

248. The method of embodiment 245, wherein the dialogue agent comprisesan avatar identity on a social media platform.

249. The method of embodiment 245, further comprising:

creating a digital asset wrapper comprising the captured interactivedialogue.

250. The method of embodiment 245, wherein the digital asset is one of aconversation asset, an artificial intelligence entity asset, a portfolioasset and an exchange asset.

251. The method of embodiment 245, wherein the instantiation of thecreated digital asset comprises:

receiving asset information of the digital asset;

obtaining corporate certificate and credentials from an owner of thedigital asset;

indentifying a negotiator for a transaction; and

assigning shares of the digital asset to a negotiator to engage in thetransaction.

252. The method of embodiment 245, wherein the instantiation furthercomprises:

determining cost factors of the digital asset.

253. The method of embodiment 252, wherein the instantiation furthercomprises:

determining a dividends payment structured based on the cost factors.

254. The method of embodiment 245, wherein the instantiation furthercomprises:

establishing intellectual property right to an investor.

255. The method of embodiment 245, wherein the financial instrumentcomprises one of a future, a forward and an option.

256. The method of embodiment 245, wherein the financial instrumentcomprises stock shares of the digital asset.

257. The method of embodiment 245, wherein the index of the financialinstrument is measured in dialogue value units.

258. The method of embodiment 245, wherein the index of the financialinstrument is a dollar value.

259. The method of embodiment 245, wherein the financial instrument istraded on a financial trading platform.

260. A digital conversation exchange apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

capture an interactive dialogue between an individual target and adialogue agent;

create a digital asset comprising at least the captured interactivedialogue;

instantiate the created digital asset;

generate a tradable financial instrument based on the instantiateddigital asset;

determine an index of the tradable financial instrument; and

facilitate a transaction of the financial instrument between an owner ofthe digital asset and an investor.

261. The apparatus of embodiment 260, wherein the interactive dialogueis saved in a voice xml format.

262. The apparatus of embodiment 260, wherein the individual targetcomprises a smart phone.

263. The apparatus of embodiment 260, wherein the dialogue agentcomprises an avatar identity on a social media platform.

264. The apparatus of embodiment 260, wherein the processor furtherissues instructions to:

creating a digital asset wrapper comprising the captured interactivedialogue.

265. The apparatus of embodiment 260, wherein the digital asset is oneof a conversation asset, an artificial intelligence entity asset, aportfolio asset and an exchange asset.

266. The apparatus of embodiment 260, wherein the instantiation of thecreated digital asset comprises:

receiving asset information of the digital asset;

obtaining corporate certificate and credentials from an owner of thedigital asset;

indentifying a negotiator for a transaction; and

assigning shares of the digital asset to a negotiator to engage in thetransaction.

267. The apparatus of embodiment 260, wherein the instantiation furthercomprises:

determining cost factors of the digital asset.

268. The apparatus of embodiment 267, wherein the instantiation furthercomprises:

determining a dividends payment structured based on the cost factors.

269. The apparatus of embodiment 260, wherein the instantiation furthercomprises:

establishing intellectual property right to an investor.

270. The apparatus of embodiment 260, wherein the financial instrumentcomprises one of a future, a forward and an option.

271. The apparatus of embodiment 260, wherein the financial instrumentcomprises stock shares of the digital asset.

272. The apparatus of embodiment 260, wherein the index of the financialinstrument is measured in dialogue value units.

273. The apparatus of embodiment 260, wherein the index of the financialinstrument is a dollar value.

274. The apparatus of embodiment 260, wherein the financial instrumentis traded on a financial trading platform.

275. A digital conversation exchange system embodiment, comprising:

means to capture an interactive dialogue between an individual targetand a dialogue agent;

means to create a digital asset comprising at least the capturedinteractive dialogue;

means to instantiate the created digital asset;

means to generate a tradable financial instrument based on theinstantiated digital asset;

means to determine an index of the tradable financial instrument; and

means to facilitate a transaction of the financial instrument between anowner of the digital asset and an investor.

276. The system of embodiment 275, wherein the interactive dialogue issaved in a voice xml format.

277. The system of embodiment 275, wherein the individual targetcomprises a smart phone.

278. The system of embodiment 275, wherein the dialogue agent comprisesan avatar identity on a social media platform.

279. The system of embodiment 275, further comprising:

creating a digital asset wrapper comprising the captured interactivedialogue.

280. The system of embodiment 275, wherein the digital asset is one of aconversation asset, an artificial intelligence entity asset, a portfolioasset and an exchange asset.

281. The system of embodiment 275, wherein the instantiation of thecreated digital asset comprises:

receiving asset information of the digital asset;

obtaining corporate certificate and credentials from an owner of thedigital asset;

indentifying a negotiator for a transaction; and

assigning shares of the digital asset to a negotiator to engage in thetransaction.

282. The system of embodiment 275, wherein the instantiation furthercomprises:

determining cost factors of the digital asset.

283. The system of embodiment 282, wherein the instantiation furthercomprises:

determining a dividends payment structured based on the cost factors.

284. The system of embodiment 275, wherein the instantiation furthercomprises:

establishing intellectual property right to an investor.

285. The system of embodiment 275, wherein the financial instrumentcomprises one of a future, a forward and an option.

286. The system of embodiment 275, wherein the financial instrumentcomprises stock shares of the digital asset.

287. The system of embodiment 275, wherein the index of the financialinstrument is measured in dialogue value units.

288. The system of embodiment 275, wherein the index of the financialinstrument is a dollar value.

289. The system of embodiment 275, wherein the financial instrument istraded on a financial trading platform.

290. A digital conversation exchange processor-readable mediumembodiment storing processor-issuable instructions to:

capture an interactive dialogue between an individual target and adialogue agent;

create a digital asset comprising at least the captured interactivedialogue;

instantiate the created digital asset;

generate a tradable financial instrument based on the instantiateddigital asset;

determine an index of the tradable financial instrument; and

facilitate a transaction of the financial instrument between an owner ofthe digital asset and an investor.

291. The medium of embodiment 290, wherein the interactive dialogue issaved in a voice xml format.

292. The medium of embodiment 290, wherein the individual targetcomprises a smart phone.

293. The medium of embodiment 290, wherein the dialogue agent comprisesan avatar identity on a social media platform.

294. The medium of embodiment 290, further comprising:

creating a digital asset wrapper comprising the captured interactivedialogue.

295. The medium of embodiment 290, wherein the digital asset is one of aconversation asset, an artificial intelligence entity asset, a portfolioasset and an exchange asset.

296. The medium of embodiment 290, wherein the instantiation of thecreated digital asset comprises:

receiving asset information of the digital asset;

obtaining corporate certificate and credentials from an owner of thedigital asset;

indentifying a negotiator for a transaction; and

assigning shares of the digital asset to a negotiator to engage in thetransaction.

297. The medium of embodiment 290, wherein the instantiation furthercomprises:

determining cost factors of the digital asset.

298. The medium of embodiment 297, wherein the instantiation furthercomprises:

determining a dividends payment structured based on the cost factors.

299. The medium of embodiment 290, wherein the instantiation furthercomprises:

establishing intellectual property right to an investor.

300. The medium of embodiment 290, wherein the financial instrumentcomprises one of a future, a forward and an option.

301. The medium of embodiment 290, wherein the financial instrumentcomprises stock shares of the digital asset.

302. The medium of embodiment 290, wherein the index of the financialinstrument is measured in dialogue value units.

303. The medium of embodiment 290, wherein the index of the financialinstrument is a dollar value.

304. The medium of embodiment 290, wherein the financial instrument istraded on a financial trading platform.

305. A digital conversation exchange processor-implemented methodembodiment, comprising:

submitting a demand for a digital asset to a financial trading platform;

receiving financial information of tradable financial instrumentsrelated to the demanded digital asset;

submitting credential information associated with an investor;

proposing a transaction with regard to a tradable financial instrumentrelated to the demanded digital asset; and

completing the proposed transaction via the financial trading platform.

306. A digital conversation exchange apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

submit a demand for a digital asset to a financial trading platform;

receive financial information of tradable financial instruments relatedto the demanded digital asset;

submit credential information associated with an investor;

propose a transaction with regard to a tradable financial instrumentrelated to the demanded digital asset; and

complete the proposed transaction via the financial trading platform.

307. A digital conversation exchange system embodiment, comprising:

means to submit a demand for a digital asset to a financial tradingplatform;

means to receive financial information of tradable financial instrumentsrelated to the demanded digital asset;

means to submit credential information associated with an investor;

means to propose a transaction with regard to a tradable financialinstrument related to the demanded digital asset; and

means to complete the proposed transaction via the financial tradingplatform.

308. A digital conversation exchange processor-readable mediumembodiment storing processor-issuable instructions to:

submit a demand for a digital asset to a financial trading platform;

receive financial information of tradable financial instruments relatedto the demanded digital asset;

submit credential information associated with an investor;

propose a transaction with regard to a tradable financial instrumentrelated to the demanded digital asset; and

complete the proposed transaction via the financial trading platform.

309. A digital conversation pricing processor-implemented methodembodiment, comprising:

retrieving a digital dialogue between an individual target and adialogue agent;

determining a plurality of parameters associated with the digitaldialogue;

allocating a value point to each dialogue step of the digital dialogue;

receiving trading information from a trading platform;

adjusting the allocated value point of each dialogue step based on thereceived trading information.

310. The method of embodiment 309, wherein the dialogue agent comprisesan avatar identity on a social platform.

311. The method of embodiment 309, wherein digital dialogue is saved ina voice XML format.

312. The method of embodiment 309, wherein the plurality of parameterscomprises a pathway of the dialogue.

313. The method of embodiment 312, wherein the pathway is associatedwith a starting node and an ending node.

314. The method of embodiment 309, wherein the plurality of parameterscomprises a number of dialogue steps in the dialogue.

315. The method of embodiment 309, wherein the plurality of parameterscomprises an amount of time taken for each dialogue step.

316. The method of embodiment 309, wherein the value point allocated toeach dialogue step is determined based on an outcome of the dialogue.

317. The method of embodiment 309, wherein the value point comprises adialogue value metric.

318. The method of embodiment 309, wherein the value point comprises adollar value.

319. The method of embodiment 309, further comprising:

querying for related dialogue on the received trading information ofdigital assets.

320. The method of embodiment 309, wherein the adjusting the allocatedvalue point of each dialogue step is based on a supply-demandrelationship reflected by the received trading information.

321. A digital conversation pricing apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

retrieve a digital dialogue between an individual target and a dialogueagent;

determine a plurality of parameters associated with the digitaldialogue;

allocate a value point to each dialogue step of the digital dialogue;

receive trading information from a trading platform;

adjust the allocated value point of each dialogue step based on thereceived trading information.

322. The apparatus of embodiment 321, wherein the dialogue agentcomprises an avatar identity on a social platform.

323. The apparatus of embodiment 321, wherein digital dialogue is savedin a voice XML format.

324. The apparatus of embodiment 321, wherein the plurality ofparameters comprises a pathway of the dialogue.

325. The apparatus of embodiment 324, wherein the pathway is associatedwith a starting node and an ending node.

326. The apparatus of embodiment 321, wherein the plurality ofparameters comprises a number of dialogue steps in the dialogue.

327. The apparatus of embodiment 321, wherein the plurality ofparameters comprises an amount of time taken for each dialogue step.

328. The apparatus of embodiment 321, wherein the value point allocatedto each dialogue step is determined based on an outcome of the dialogue.

329. The apparatus of embodiment 321, wherein the value point comprisesa dialogue value metric.

330. The apparatus of embodiment 321, wherein the value point comprisesa dollar value.

331. The apparatus of embodiment 321, wherein the processor furtherissues instructions for:

querying for related dialogue on the received trading information ofdigital assets.

332. The apparatus of embodiment 321, wherein the adjusting theallocated value point of each dialogue step is based on a supply-demandrelationship reflected by the received trading information.

333. A digital conversation pricing system embodiment, comprising:

means to retrieve a digital dialogue between an individual target and adialogue agent;

means to determine a plurality of parameters associated with the digitaldialogue;

means to allocate a value point to each dialogue step of the digitaldialogue;

means to receive trading information from a trading platform;

means to adjust the allocated value point of each dialogue step based onthe received trading information.

334. The system of embodiment 333, wherein the dialogue agent comprisesan avatar identity on a social platform.

335. The system of embodiment 333, wherein digital dialogue is saved ina voice XML format.

336. The system of embodiment 333, wherein the plurality of parameterscomprises a pathway of the dialogue.

337. The system of embodiment 336, wherein the pathway is associatedwith a starting node and an ending node.

338. The system of embodiment 333, wherein the plurality of parameterscomprises a number of dialogue steps in the dialogue.

339. The system of embodiment 333, wherein the plurality of parameterscomprises an amount of time taken for each dialogue step.

340. The system of embodiment 333, wherein the value point allocated toeach dialogue step is determined based on an outcome of the dialogue.

341. The system of embodiment 333, wherein the value point comprises adialogue value metric.

342. The system of embodiment 333, wherein the value point comprises adollar value.

343. The system of embodiment 333, further comprising:

querying for related dialogue on the received trading information ofdigital assets.

344. The system of embodiment 333, wherein the adjusting the allocatedvalue point of each dialogue step is based on a supply-demandrelationship reflected by the received trading information.

345. A digital conversation pricing processor-readable medium embodimentstoring processor-issuable instructions to:

retrieve a digital dialogue between an individual target and a dialogueagent;

determine a plurality of parameters associated with the digitaldialogue;

allocate a value point to each dialogue step of the digital dialogue;

receive trading information from a trading platform;

adjust the allocated value point of each dialogue step based on thereceived trading information.

346. The medium of embodiment 345, wherein the dialogue agent comprisesan avatar identity on a social platform.

347. The medium of embodiment 345, wherein digital dialogue is saved ina voice XML format.

348. The medium of embodiment 345, wherein the plurality of parameterscomprises a pathway of the dialogue.

349. The medium of embodiment 348, wherein the pathway is associatedwith a starting node and an ending node.

350. The medium of embodiment 345, wherein the plurality of parameterscomprises a number of dialogue steps in the dialogue.

351. The medium of embodiment 345, wherein the plurality of parameterscomprises an amount of time taken for each dialogue step.

352. The medium of embodiment 345, wherein the value point allocated toeach dialogue step is determined based on an outcome of the dialogue.

353. The medium of embodiment 345, wherein the value point comprises adialogue value metric.

354. The medium of embodiment 345, wherein the value point comprises adollar value.

355. The medium of embodiment 345, further comprising:

querying for related dialogue on the received trading information ofdigital assets.

356. The medium of embodiment 345, wherein the adjusting the allocatedvalue point of each dialogue step is based on a supply-demandrelationship reflected by the received trading information.

357. A digital conversation management processor-implemented methodembodiment, comprising:

initializing a dialogue agent application with an individual target;

receiving a dialogue action from the individual target;

connecting to a search engine for a query based on the dialogue action;

generating a dialogue response comprising a link of search results onthe search engine if the search results are available; and

generating a dialogue response comprising a link of related topics ifthe search results are not available.

358. The method of embodiment 357, wherein the dialogue agentapplication is initialized on a social media platform.

359. The method of embodiment 357, wherein the dialogue agentapplication is initialized on a mobile platform.

360. The method of embodiment 357, further comprising:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

361. The method of embodiment 357, wherein the dialogue action comprisesan inquiry for information.

362. The method of embodiment 357, further comprising:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

363. The method of embodiment 357, further comprising:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

364. The method of embodiment 357, further comprising:

determining a conversation unit value of the interactive dialogue basedon the pathway.

365. The method of embodiment 357, further comprising:

generating a dialogue response comprising a link to another dialogueagent if the search results are not available.

366. The method of embodiment 357, further comprising:

updating a knowledge record with the search results.

367. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

initialize a dialogue agent application with an individual target;

receive a dialogue action from the individual target;

connect to a search engine for a query based on the dialogue action;

generate a dialogue response comprising a link of search results on thesearch engine if the search results are available; and

generate a dialogue response comprising a link of related topics if thesearch results are not available.

368. The apparatus of embodiment 367, wherein the dialogue agentapplication is initialized on a social media platform.

369. The apparatus of embodiment 367, wherein the dialogue agentapplication is initialized on a mobile platform.

370. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

371. The apparatus of embodiment 367, wherein the dialogue actioncomprises an inquiry for information.

372. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

373. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

374. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

375. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

generating a dialogue response comprising a link to another dialogueagent if the search results are not available.

376. The apparatus of embodiment 367, wherein the processor furtherissues instructions for:

updating a knowledge record with the search results.

377. A digital conversation pricing system embodiment, comprising:

means to initialize a dialogue agent application with an individualtarget;

means to receive a dialogue action from the individual target;

means to connect to a search engine for a query based on the dialogueaction;

means to generate a dialogue response comprising a link of searchresults on the search engine if the search results are available; and

means to generate a dialogue response comprising a link of relatedtopics if the search results are not available

378. The system of embodiment 377, wherein the dialogue agentapplication is initialized on a social media platform.

379. The system of embodiment 377, wherein the dialogue agentapplication is initialized on a mobile platform.

380. The system of embodiment 377, further comprising means for:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

381. The system of embodiment 377, wherein the dialogue action comprisesan inquiry for information.

382. The system of embodiment 377, further comprising means for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

383. The system of embodiment 377, further comprising means for:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

384. The system of embodiment 377, further comprising means for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

385. The system of embodiment 377, further comprising means for:

generating a dialogue response comprising a link to another dialogueagent if the search results are not available.

386. The system of embodiment 377, further comprising means for:

updating a knowledge record with the search results.

387. A digital conversation pricing processor-readable medium embodimentstoring processor-issuable instructions to:

initialize a dialogue agent application with an individual target;

receive a dialogue action from the individual target;

connect to a search engine for a query based on the dialogue action;

generate a dialogue response comprising a link of search results on thesearch engine if the search results are available; and

generate a dialogue response comprising a link of related topics if thesearch results are not available.

388. The medium of embodiment 387, wherein the dialogue agentapplication is initialized on a social media platform.

389. The medium of embodiment 387, wherein the dialogue agentapplication is initialized on a mobile platform.

390. The medium of embodiment 387, further storing instructions for:

generating a web service;

creating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

391. The medium of embodiment 387, wherein the dialogue action comprisesan inquiry for information.

392. The medium of embodiment 387, further storing instructions for:

determining a condition associated with the received dialogue line; and

retrieve an optional dialogue line in response to the determinedcondition.

393. The medium of embodiment 387, further storing instructions for:

determining a pathway of the recorded interactive dialogue; and

determining a plurality of parameters associated with the interactivedialogue.

394. The medium of embodiment 387, further storing instructions for:

determining a conversation unit value of the interactive dialogue basedon the pathway.

395. The medium of embodiment 387, further storing instructions for:

generating a dialogue response comprising a link to another dialogueagent if the search results are not available.

396. The medium of embodiment 387, further storing instructions for:

updating a knowledge record with the search results.

397. A digital conversation management processor-implemented methodembodiment, comprising:

initializing a dialogue with a dialogue agent on a dialogue platform;

submitting a dialogue action comprising an inquiry;

receiving a dialogue response comprising a link of search results on thesearch engine if the search results are available; and

receiving a dialogue response comprising a link of related topics if thesearch results are not available.

398. The method of embodiment 397, wherein dialogue agent application isinitialized on a social media platform.

399. The method of embodiment 397, wherein the dialogue agentapplication is initialized on a mobile platform.

400. The method of embodiment 397, further comprising:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

401. The method of embodiment 397, wherein the dialogue action comprisesan inquiry for information.

402. A digital conversation management apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

initialize a dialogue with a dialogue agent on a dialogue platform;

submit a dialogue action comprising an inquiry;

receive a dialogue response comprising a link of search results on thesearch engine if the search results are available; and

receive a dialogue response comprising a link of related topics if thesearch results are not available.

403. The apparatus of embodiment 402, wherein dialogue agent applicationis initialized on a social media platform.

404. The apparatus of embodiment 402, wherein the dialogue agentapplication is initialized on a mobile platform.

405. The apparatus of embodiment 402, further comprising:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

406. The apparatus of embodiment 402, wherein the dialogue actioncomprises an inquiry for information.

407. A digital conversation pricing system embodiment, comprising:

means to initialize a dialogue with a dialogue agent on a dialogueplatform;

means to submit a dialogue action comprising an inquiry;

means to receive a dialogue response comprising a link of search resultson the search engine if the search results are available; and

means to receive a dialogue response comprising a link of related topicsif the search results are not available.

408. The system of embodiment 407, wherein dialogue agent application isinitialized on a social media platform.

409. The system of embodiment 407, wherein the dialogue agentapplication is initialized on a mobile platform.

410. The system of embodiment 407, further comprising:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

411. The system of embodiment 407, wherein the dialogue action comprisesan inquiry for information.

412. A digital conversation management processor-readable mediumembodiment storing processor-issuable instructions to:

initialize a dialogue with a dialogue agent on a dialogue platform;

submit a dialogue action comprising an inquiry;

receive a dialogue response comprising a link of search results on thesearch engine if the search results are available; and

receive a dialogue response comprising a link of related topics if thesearch results are not available.

413. The medium of embodiment 412, wherein dialogue agent application isinitialized on a social media platform.

414. The medium of embodiment 412, wherein the dialogue agentapplication is initialized on a mobile platform.

415. The medium of embodiment 412, further comprising:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

416. The medium of embodiment 412, wherein the dialogue action comprisesan inquiry for information.

417. A digital conversation management processor-implemented methodcomprising:

initializing an dialogue agent application on a dialogue platform;

capturing a search request from the dialogue agent, the search requestcomprising a key word;

retrieving previously stored information related to the key word;

receiving a list of search results linked to a search engine based onthe key word; and

incorporating information from the list of search results in a recordrelated to the key word.

418. The method of embodiment 417, further comprising:

populating the dialogue agent application on social media; and

implement the dialogue agent to capture interactive dialogue actions.

419. The method of embodiment 417, further comprising:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

420. The method of embodiment 417, further comprising dialogue cloudwith key words for search engines.

421. The method of embodiment 417, further comprising:

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

422. The method of embodiment 417, wherein the dialogue agent is anavatar on a social media platform.

423. The method of embodiment 417, further comprising:

registering the conversation on a virtual asset exchange platform.

424. The method of embodiment 417, further comprising:

registering the conversation on a financial trading platform.

425. The method of embodiment 417, further comprising:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

426. The method of embodiment 425, wherein the search comprises a keyword based Google search.

427. The method of embodiment 417, further comprising:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

428. The method of embodiment 417, further comprising:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

429. The method of embodiment 417, further comprising:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

430. The method of embodiment 417, further comprising:

receiving information from another dialogue agent; and

incorporating information from the other dialogue agent in a recordrelated to the key word

431. A digital conversation management apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

initialize an dialogue agent application on a dialogue platform;

capture a search request from the dialogue agent, the search requestcomprising a key word;

retrieve previously stored information related to the key word;

receive a list of search results linked to a search engine based on thekey word; and

incorporate information from the list of search results in a recordrelated to the key word.

432. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

populating the dialogue agent application on social media; and

implement the dialogue agent to capture interactive dialogue actions.

433. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

434. The apparatus of embodiment 431, wherein the processor furtherissues instructions for dialogue cloud with key words for searchengines.

435. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

436. The apparatus of embodiment 431, wherein the dialogue agent is anavatar on a social media platform.

437. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

registering the conversation on a virtual asset exchange platform.

438. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

registering the conversation on a financial trading platform.

439. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

440. The apparatus of embodiment 439, wherein the search comprises a keyword based Google search.

441. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

442. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

443. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

444. The apparatus of embodiment 431, wherein the processor furtherissues instructions for:

receiving information from another dialogue agent; and

incorporating information from the other dialogue agent in a recordrelated to the key word

445. A digital conversation management system embodiment, comprising:

means to initialize an dialogue agent application on a dialogueplatform;

means to capture a search request from the dialogue agent, the searchrequest comprising a key word;

means to retrieve previously stored information related to the key word;

means to receive a list of search results linked to a search enginebased on the key word; and

means to incorporate information from the list of search results in arecord related to the key word.

446. The system of embodiment 445, further comprising means for:

populating the dialogue agent application on social media; and

implement the dialogue agent to capture interactive dialogue actions.

447. The system of embodiment 445, further comprising means for:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

448. The system of embodiment 445, further comprising means for dialoguecloud with key words for search engines.

449. The system of embodiment 445, further comprising means for:

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

450. The system of embodiment 445, wherein the dialogue agent is anavatar on a social media platform.

451. The system of embodiment 445, further comprising means for:

registering the conversation on a virtual asset exchange platform.

452. The system of embodiment 445, further comprising means for:

registering the conversation on a financial trading platform.

453. The system of embodiment 445, further comprising means for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

454. The system of embodiment 453, wherein the search comprises a keyword based Google search.

455. The system of embodiment 445, further comprising means for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

456. The system of embodiment 445, further comprising means for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

457. The system of embodiment 445, further comprising means for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

458. The system of embodiment 445, further comprising means for:

receiving information from another dialogue agent; and

incorporating information from the other dialogue agent in a recordrelated to the key word.

459. A digital conversation management processor-readable mediumembodiment storing processor-issuable instructions to:

initialize an dialogue agent application on a dialogue platform;

capture a search request from the dialogue agent, the search requestcomprising a key word;

retrieve previously stored information related to the key word;

receive a list of search results linked to a search engine based on thekey word; and

incorporate information from the list of search results in a recordrelated to the key word.

460. The medium of embodiment 459, further storing instructions for:

populating the dialogue agent application on social media; and

implement the dialogue agent to capture interactive dialogue actions.

461. The medium of embodiment 459, further storing instructions for:

generating a web service;

connecting the web-service to an avatar front end; and

completing dialogue agent application.

462. The medium of embodiment 459, further storing instructions fordialogue cloud with key words for search engines.

463. The medium of embodiment 459, further storing instructions for:

populating on a social media platform;

generating links accessible from Internet and smart phone applications;and

updating wrapper description identifications.

464. The medium of embodiment 459, wherein the dialogue agent is anavatar on a social media platform.

465. The medium of embodiment 459, further storing instructions for:

registering the conversation on a virtual asset exchange platform.

466. The medium of embodiment 459, further storing instructions for:

registering the conversation on a financial trading platform.

467. The medium of embodiment 459, further storing instructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

468. The medium of embodiment 467, wherein the search comprises a keyword based Google search.

469. The medium of embodiment 459, further storing instructions for:

providing alternate questions to the individual target to obtain furtherinformation if the search fails; and

generating a dialogue line based on partial key word search and theobtained information.

470. The medium of embodiment 459, further storing instructions for:

capturing updated product information from the Internet; and

requesting a client provide updated product information.

471. The medium of embodiment 459, further storing instructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

472. The medium of embodiment 459, further storing instructions for:

receiving information from another dialogue agent; and

incorporating information from the other dialogue agent in a recordrelated to the key word.

473. A digital conversation generating processor-implemented methodembodiment, comprising:

initializing a dialogue agent application developer user interface;

launching a dialogue tree application and a dialogue script generatingpanel;

retrieving a dialogue node in the dialogue tree;

determining a plurality of conditions associated with the dialogue node;

generating a dialogue tree by connecting the dialogue node to adifferent dialogue node based on each condition; and

completing the dialogue tree by connecting all available dialogue nodes.

474. The method of embodiment 473, wherein the dialogue agentapplication is initialized by a developer.

475. The method of embodiment 473, wherein the dialogue tree applicationand the dialogue script generating panel are launched in a slit screenvia the user interface.

476. The method of embodiment 473, wherein the dialogue tree comprises aplurality of connected dialogue nodes.

477. The method of embodiment 473, wherein the dialogue node denotes adialogue action.

478. The method of embodiment 473, wherein the dialogue node denotes adialogue outcome.

479. The method of embodiment 473, further comprising generating adecision tree.

480. The method of embodiment 479, wherein the decision tree isdetermined by a pathway on the dialogue tree via a conditional logic.

481. The method of embodiment 473, further comprising:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

482. The method of embodiment 473, further comprising:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

483. The method of embodiment 473, further comprising:

dialogue cloud with key words for search engines.

484. The method of embodiment 473, further comprising:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

485. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

initialize a dialogue agent application developer user interface;

launch a dialogue tree application and a dialogue script generatingpanel;

retrieve a dialogue node in the dialogue tree;

determine a plurality of conditions associated with the dialogue node;

generate a dialogue tree by connecting the dialogue node to a differentdialogue node based on each condition; and

complete the dialogue tree by connecting all available dialogue nodes.

486. The apparatus of embodiment 485, wherein the dialogue agentapplication is initialized by a developer.

487. The apparatus of embodiment 485, wherein the dialogue treeapplication and the dialogue script generating panel are launched in aslit screen via the user interface.

488. The apparatus of embodiment 485, wherein the dialogue treecomprises a plurality of connected dialogue nodes.

489. The apparatus of embodiment 485, wherein the dialogue node denotesa dialogue action.

490. The apparatus of embodiment 485, wherein the dialogue node denotesa dialogue outcome.

491. The apparatus of embodiment 485, wherein the processor furtherissues instructions for generating a decision tree.

492. The apparatus of embodiment 491, wherein the decision tree isdetermined by a pathway on the dialogue tree via a conditional logic.

493. The apparatus of embodiment 485, wherein the processor furtherissues instructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

494. The apparatus of embodiment 485, wherein the processor furtherissues instructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

495. The apparatus of embodiment 485, wherein the processor furtherissues instructions for:

dialogue cloud with key words for search engines.

496. The apparatus of embodiment 485, wherein the processor furtherissues instructions for:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

497. A digital conversation generating system embodiment, comprising:

means to initialize a dialogue agent application developer userinterface;

means to launch a dialogue tree application and a dialogue scriptgenerating panel;

means to retrieve a dialogue node in the dialogue tree;

means to determine a plurality of conditions associated with thedialogue node;

means to generate a dialogue tree by connecting the dialogue node to adifferent dialogue node based on each condition; and

means to complete the dialogue tree by connecting all available dialoguenodes.

498. The system of embodiment 497, wherein the dialogue agentapplication is initialized by a developer.

499. The system of embodiment 497, wherein the dialogue tree applicationand the dialogue script generating panel are launched in a slit screenvia the user interface.

500. The system of embodiment 497, wherein the dialogue tree comprises aplurality of connected dialogue nodes.

501. The system of embodiment 497, wherein the dialogue node denotes adialogue action.

502. The system of embodiment 497, wherein the dialogue node denotes adialogue outcome.

503. The system of embodiment 497, further comprising means forgenerating a decision tree.

504. The system of embodiment 503, wherein the decision tree isdetermined by a pathway on the dialogue tree via a conditional logic.

505. The system of embodiment 497, further comprising means for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

506. The system of embodiment 497, further comprising means for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

507. The system of embodiment 497, further comprising means for:

dialogue cloud with key words for search engines.

508. The system of embodiment 497, further comprising means for:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

509. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

initialize a dialogue agent application developer user interface;

launch a dialogue tree application and a dialogue script generatingpanel;

retrieve a dialogue node in the dialogue tree;

determine a plurality of conditions associated with the dialogue node;

generate a dialogue tree by connecting the dialogue node to a differentdialogue node based on each condition; and

complete the dialogue tree by connecting all available dialogue nodes.

510. The medium of embodiment 509, wherein the dialogue agentapplication is initialized by a developer.

511. The medium of embodiment 509, wherein the dialogue tree applicationand the dialogue script generating panel are launched in a slit screenvia the user interface.

512. The medium of embodiment 509, wherein the dialogue tree comprises aplurality of connected dialogue nodes.

513. The medium of embodiment 509, wherein the dialogue node denotes adialogue action.

514. The medium of embodiment 509, wherein the dialogue node denotes adialogue outcome.

515. The medium of embodiment 509, wherein the processor further issuesinstructions for generating a decision tree.

516. The medium of embodiment 515, wherein the decision tree isdetermined by a pathway on the dialogue tree via a conditional logic.

517. The medium of embodiment 509, wherein the processor further issuesinstructions for:

initiating dialogue analytics to drive individual-agent interactions;

determining a dialogue pathway of a dialogue; and

determining dialogue parameters based on the dialogue pathway.

518. The medium of embodiment 509, wherein the processor further issuesinstructions for:

initiating a search to obtain information for the conversation; and

generating a hyperlink outcome based on the search results.

519. The medium of embodiment 509, wherein the processor further issuesinstructions for:

dialogue cloud with key words for search engines.

520. The medium of embodiment 509, wherein the processor further issuesinstructions for:

connecting to a web service;

associating an avatar identity on the dialogue platform; and

connecting the web-service to the avatar identity.

521. A digital conversation generating processor-readable methodembodiment, comprising:

obtaining an initial prompt for use in an artificial intelligence agentdialogue;

obtaining a plurality of agent dialogue conditions;

specifying a condition trigger for the plurality of agent dialogueconditions;

providing a subsequent prompt for each triggered conditional dialoguebranch;

obtaining a search link for each triggered conditional dialogue branch;and

sending the obtained initial prompt, the plurality of agent dialogueconditions, each specified condition trigger, the subsequent prompt foreach triggered conditional dialogue branch, the search link to a serverfor dialogue agent registration.

522. The method of embodiment 521, wherein the initial prompt isreceived from a user.

523. The method of embodiment 521, wherein the initial prompt isobtained from Wiki submission from a plurality of users.

524. The method of embodiment 521, wherein the search link is generatedby a query on a search engine.

525. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to: obtaining an initialprompt for use in an artificial intelligence agent dialogue;

obtaining a plurality of agent dialogue conditions;

obtaining a specified condition trigger for the plurality of agentdialogue conditions;

obtaining a subsequent prompt for each triggered conditional dialoguebranch;

obtaining a search link for each triggered conditional dialogue branch;and

sending the obtained initial prompt, the plurality of agent dialogueconditions, each specified condition trigger, the subsequent prompt foreach triggered conditional dialogue branch, the search link to a serverfor dialogue agent registration.

526. The apparatus of embodiment 525, wherein the initial prompt isreceived from a user.

527. The apparatus of embodiment 525, wherein the initial prompt isobtained from Wiki submission from a plurality of users.

528. The apparatus of embodiment 525, wherein the search link isgenerated by a query on a search engine.

529. A digital conversation generating system embodiment, comprising:

means to obtain an initial prompt for use in an artificial intelligenceagent dialogue;

means to obtain a plurality of agent dialogue conditions;

means to obtain a specified condition trigger for the plurality of agentdialogue conditions;

means to obtain a subsequent prompt for each triggered conditionaldialogue branch;

means to obtain a search link for each triggered conditional dialoguebranch; and

means to send the obtained initial prompt, the plurality of agentdialogue conditions, each specified condition trigger, the subsequentprompt for each triggered conditional dialogue branch, the search linkto a server for dialogue agent registration.

530. The system of embodiment 529, wherein the initial prompt isreceived from a user.

531. The system of embodiment 529, wherein the initial prompt isobtained from Wiki submission from a plurality of users.

532. The system of embodiment 529, wherein the search link is generatedby a query on a search engine.

533. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

obtain an initial prompt for use in an artificial intelligence agentdialogue;

obtain a plurality of agent dialogue conditions;

obtain a specified condition trigger for the plurality of agent dialogueconditions;

obtain a subsequent prompt for each triggered conditional dialoguebranch;

obtain a search link for each triggered conditional dialogue branch; and

send the obtained initial prompt, the plurality of agent dialogueconditions, each specified condition trigger, the subsequent prompt foreach triggered conditional dialogue branch, the search link to a serverfor dialogue agent registration.

534. The medium of embodiment 533, wherein the initial prompt isreceived from a user.

535. The medium of embodiment 533, wherein the initial prompt isobtained from Wiki submission from a plurality of users.

536. The medium of embodiment 533, wherein the search link is generatedby a query on a search engine.

537. A digital conversation generating processor-readable methodembodiment, comprising:

receiving a dialogue agent registration request;

receiving a series of dialogue steps, including:

-   -   an initial prompt for use in an artificial intelligence agent        dialogue,    -   a plurality of agent dialogue conditions,    -   a condition trigger for the plurality of agent dialogue        conditions,    -   a subsequent prompt for each triggered conditional dialogue        branch, and    -   a search link for each triggered conditional dialogue branch;        and

registering the dialogue agent associated with the artificialintelligence agent dialogue.

538. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

receive a dialogue agent registration request;

receive a series of dialogue steps, including:

-   -   an initial prompt for use in an artificial intelligence agent        dialogue,    -   a plurality of agent dialogue conditions,    -   a condition trigger for the plurality of agent dialogue        conditions,    -   a subsequent prompt for each triggered conditional dialogue        branch, and    -   a search link for each triggered conditional dialogue branch;        and

register the dialogue agent associated with the artificial intelligenceagent dialogue.

539. A digital conversation generating system embodiment, comprising:

means to receive a dialogue agent registration request;

means to receive a series of dialogue steps, including:

-   -   an initial prompt for use in an artificial intelligence agent        dialogue,    -   a plurality of agent dialogue conditions,    -   a condition trigger for the plurality of agent dialogue        conditions,    -   a subsequent prompt for each triggered conditional dialogue        branch, and    -   a search link for each triggered conditional dialogue branch;        and

means to register the dialogue agent associated with the artificialintelligence agent dialogue.

540. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

receive a dialogue agent registration request;

receive a series of dialogue steps, including:

-   -   an initial prompt for use in an artificial intelligence agent        dialogue,    -   a plurality of agent dialogue conditions,    -   a condition trigger for the plurality of agent dialogue        conditions,    -   a subsequent prompt for each triggered conditional dialogue        branch, and    -   a search link for each triggered conditional dialogue branch;        and

register the dialogue agent associated with the artificial intelligenceagent dialogue.

541. A digital conversation generating processor-readable methodembodiment, comprising:

instantiating a dialogue agent loader in a search engine interface;

obtaining a search engine query on the dialogue agent database formatching dialogue search agents;

providing matching agents in a search engine query result;

instantiating a selected dialogue search agent;

providing a dialogue agent prompt via the instantiated dialogue searchagent;

obtaining responses to the dialogue agent prompt;

updating the search engine query result based on the obtained responsesby using dialogue search agent search links.

542. The method of embodiment 541, wherein the search engine query isbased on a key word submitted by a user.

543. The method of embodiment 542, wherein the key word specifies atopic for dialogue search agents.

544. The method of embodiment 541, wherein the updating the searchengine query result based on the obtained responses further comprisesrefining the search engine query based on related key words from theobtained responses.

545. The method of embodiment 542, further comprising increasing acharge to a dialogue search agent sponsor for each obtained dialogueresponse.

546. A digital conversation generating apparatus embodiment, comprising:

a memory;

a processor disposed in communication with said memory, and configuredto issue a plurality of processing instructions stored in the memory,wherein the processor issues instructions to:

instantiate a dialogue agent loader in a search engine interface;

obtain a search engine query on the dialogue agent database for matchingdialogue search agents;

provide matching agents in a search engine query result;

instantiate a selected dialogue search agent;

provide a dialogue agent prompt via the instantiated dialogue searchagent;

obtain user dialogue responses to dialogue agent prompt;

update the search engine query result based on the obtained responses byusing dialogue search agent search links.

547. The apparatus of embodiment 546, wherein the search engine query isbased on a key word submitted by a user.

548. The apparatus of embodiment 547, wherein the key word specifies atopic for dialogue search agents.

549. The apparatus of embodiment 546, wherein the updating the searchengine query result based on the obtained responses further comprisesrefining the search engine query based on related key words from theobtained responses.

550. The apparatus of embodiment 547, further comprising increasing acharge to a dialogue search agent sponsor for each obtained dialogueresponse.

551. A digital conversation generating system embodiment, comprising:

means to instantiate a dialogue agent loader in a search engineinterface;

means to obtain a search engine query on the dialogue agent database formatching dialogue search agents;

means to provide matching agents in a search engine query result;

means to instantiate a selected dialogue search agent;

means to provide a dialogue agent prompt via the instantiated dialoguesearch agent;

means to obtain user dialogue responses to the dialogue agent prompt;

means to update the search engine query result based on the obtaineduser dialogue responses by using dialogue search agent search links.

552. The system of embodiment 551, wherein the search engine query isbased on a key word submitted by a user.

553. The system of embodiment 552, wherein the key word specifies atopic for dialogue search agents.

554. The system of embodiment 551, wherein the updating the searchengine query result based on the obtained responses further comprisesrefining the search engine query based on related key words from theobtained responses.

555. The system of embodiment 552, further comprising means forincreasing a charge to a dialogue search agent sponsor for each obtaineddialogue response.

556. A digital conversation generating processor-readable mediumembodiment storing processor-issuable instructions to:

instantiate a dialogue agent loader in a search engine interface;

obtain a search engine query on the dialogue agent database for matchingdialogue search agents;

provide matching agents in a search engine query result;

instantiate a selected dialogue search agent;

provide a dialogue agent prompt via the instantiated dialogue searchagent;

obtain user dialogue responses to the dialogue agent prompt;

update the search engine query result based on the obtained userdialogue responses by using dialogue search agent search links.

557. The medium of embodiment 556, wherein the dialogue agent loaderinstantiate the dialogue search agent.

558. The medium of embodiment 556, wherein the dialogue agent loader istriggered by a user selection.

559. The medium of embodiment 556, wherein the search engine query isbased on a key word submitted by a user.

560. The medium of embodiment 559, wherein the key word specifies atopic for dialogue search agents.

561. The medium of embodiment 556, wherein the updating the searchengine query result based on the obtained responses further comprisesrefining the search engine query based on related key words from theobtained responses.

562. The medium of embodiment 559, further storing instructions forincreasing a charge to a dialogue search agent sponsor for each obtaineddialogue response.

In order to address various issues and advance the art, the entirety ofthis application for APPARATUSES, METHODS AND SYSTEMS FOR A DIGITALCONVERSATION MANAGEMENT PLATFORM (including the Cover Page, Title,Headings, Field, Background, Summary, Brief Description of the Drawings,Detailed Description, Claims, Abstract, Figures, Appendices, andotherwise) shows, by way of illustration, various embodiments in whichthe claimed innovations may be practiced. The advantages and features ofthe application are of a representative sample of embodiments only, andare not exhaustive and/or exclusive. They are presented only to assistin understanding and teach the claimed principles. It should beunderstood that they are not representative of all claimed innovations.As such, certain aspects of the disclosure have not been discussedherein. That alternate embodiments may not have been presented for aspecific portion of the innovations or that further undescribedalternate embodiments may be available for a portion is not to beconsidered a disclaimer of those alternate embodiments. It will beappreciated that many of those undescribed embodiments incorporate thesame principles of the innovations and others are equivalent. Thus, itis to be understood that other embodiments may be utilized andfunctional, logical, operational, organizational, structural and/ortopological modifications may be made without departing from the scopeand/or spirit of the disclosure. As such, all examples and/orembodiments are deemed to be non-limiting throughout this disclosure.Also, no inference should be drawn regarding those embodiments discussedherein relative to those not discussed herein other than it is as suchfor purposes of reducing space and repetition. For instance, it is to beunderstood that the logical and/or topological structure of anycombination of any program components (a component collection), othercomponents and/or any present feature sets as described in the figuresand/or throughout are not limited to a fixed operating order and/orarrangement, but rather, any disclosed order is exemplary and allequivalents, regardless of order, are contemplated by the disclosure.Furthermore, it is to be understood that such features are not limitedto serial execution, but rather, any number of threads, processes,services, servers, and/or the like that may execute asynchronously,concurrently, in parallel, simultaneously, synchronously, and/or thelike are contemplated by the disclosure. As such, some of these featuresmay be mutually contradictory, in that they cannot be simultaneouslypresent in a single embodiment. Similarly, some features are applicableto one aspect of the innovations, and inapplicable to others. Inaddition, the disclosure includes other innovations not presentlyclaimed. Applicant reserves all rights in those presently unclaimedinnovations including the right to claim such innovations, fileadditional applications, continuations, continuations in part,divisions, and/or the like thereof. As such, it should be understoodthat advantages, embodiments, examples, functional, features, logical,operational, organizational, structural, topological, and/or otheraspects of the disclosure are not to be considered limitations on thedisclosure as defined by the claims or limitations on equivalents to theclaims. It is to be understood that, depending on the particular needsand/or characteristics of a DCM-Platform individual and/or enterpriseuser, database configuration and/or relational model, data type, datatransmission and/or network framework, syntax structure, and/or thelike, various embodiments of the DCM-Platform, may be implemented thatenable a great deal of flexibility and customization. For example,aspects of the DCM-Platform may be adapted for virtual commoditiespacketizing and pricing. While various embodiments and discussions ofthe DCM-Platform have been directed to artificial intelligence assetmanagement, however, it is to be understood that the embodimentsdescribed herein may be readily configured and/or customized for a widevariety of other applications and/or implementations.

1-20. (canceled)
 21. A digital conversation generationprocessor-implemented method, comprising: creating a dialogue agent;populating the created dialogue agent application on a dialogueplatform; receiving a dialogue action from an individual target via thedialogue platform; generating a dialogue line in response to thereceived dialogue action via the dialogue agent; recording aninteractive dialogue comprising the dialogue action and the generateddialogue line; retrieving the recorded interactive dialogue between theindividual target and the dialogue agent; determining a plurality ofparameters associated with the interactive dialogue; allocating a valuepoint to each dialogue element of the interactive dialogue; receivingpricing information from an exchange; adjusting the allocated valuepoint of each dialogue element based on the received pricinginformation; creating a digital asset comprising at least the retrievedinteractive dialogue associated with the allocated value point to eachdialogue element of the interactive dialogue; receiving informationindicating a demand for a digital conversation asset; determining a typeof the demanded digital conversation asset; initializing an exchangeprocedure for the determined type of the demanded digital conversationasset; obtaining information required by the exchange procedure for thedetermined type of the demanded digital conversation asset; anddetermining a value for the demanded digital conversation asset at leastbased on the obtained information for the determined type of thedemanded digital conversation asset and the allocated value point toeach dialogue element of the interactive dialogue; instantiating thecreated digital asset; generating a tradable financial instrument basedon the instantiated digital asset; determining a price for the tradablefinancial instrument; and facilitate a transaction of the financialinstrument between an owner of the digital asset and a participant. 22.A digital conversation generation processor-implemented method,comprising: creating a dialogue agent; populating the created dialogueagent application on a dialogue platform; receiving a dialogue actionfrom an individual target via the dialogue platform; generating adialogue line in response to the received dialogue action via thedialogue agent; recording an interactive dialogue comprising thedialogue action and the generated dialogue line; retrieving the recordedinteractive dialogue between the individual target and the dialogueagent; allocating a value point to each dialogue element of theinteractive dialogue; creating a digital conversation asset comprisingat least the retrieved interactive dialogue associated with theallocated value point to each dialogue element of the interactivedialogue; determining a value for the digital conversation asset atleast based on the allocated value point to each dialogue element of theinteractive dialogue; and providing the created digital conversationasset associated with the determined value for exchange.
 23. The methodof claim 22, wherein the dialogue agent is created based on anadvertising client request.
 24. The method of claim 22, wherein thecreating the dialogue agent comprises: generating a network-basedplatform; connecting the network-based platform to a dialogue agentfront end; and completing dialogue agent application.
 25. The method ofclaim 24, wherein the dialogue agent application further comprisesdialogue cloud with key words for search engines, and the populating thecreated dialogue agent application comprises: populating on a socialmedia platform; generating links accessible from Internet and smartphone applications; and updating wrapper description identifications.26. The method of claim 22, wherein the interactive dialogue is saved ina voice xml format.
 27. The method of claim 22, wherein the dialogueaction comprises an inquiry for information from any of a human beingand a system.
 28. The method of claim 22, wherein the dialogue linecomprises any of a hyperlink connected to a search engine and ahyperlink connected to another dialogue agent application.
 29. Themethod of claim 22, wherein the dialogue action is recorded with a firsttime and date stamp, and the generated dialogue line is recorded with asecond time and date stamp.
 30. The method of claim 22, wherein thevalue point to each dialogue element of the interactive dialogue isdetermined based on a conversation unit value associated with a dialoguepathway of the interactive dialogue.
 31. The method of claim 22, furthercomprising: creating a digital asset wrapper comprising the capturedinteractive dialogue.
 32. The method of claim 22, wherein the dialogueline may include any of textual contents, audio contents, pictures,video contents, multimedia contents, appointments, advertisements, anengageable reference to a transaction and engageable references tointeractive applications.
 33. The method of claim 22, furthercomprising: obtaining a cash stream from the recorded interactivedialogue, said cash stream comprising a commission made by the dialogueagent for any of presenting, converting digital service to individualtargets, and obtaining individualized information, wherein the cashstream is obtained from making dialogue agents available through anadvertising network.
 34. The method of claim 22, further comprising:receiving a client request to purchase dialogue agent service;determining a plurality of dialogue agent parameters based on the clientrequest; creating a dialogue agent application; populating the createddialogue agent application on a dialogue platform; and implementing thedialogue agent application on the dialogue platform with an individualtarget.
 35. The method of claim 34, wherein the client request comprisesa subscription request.
 36. The method of claim 22, further comprising:retrieving a digital dialogue between the individual target and thedialogue agent; determining a plurality of parameters associated withthe digital dialogue; allocating a value point to each dialogue elementof the digital dialogue; receiving trading information from a tradingplatform; adjusting the allocated value point of each dialogue elementbased on the received trading information.
 37. The method of claim 22,wherein the dialogue action comprises a search request associated with akey word.
 38. The method of claim 37, wherein the dialogue line inresponse to the received dialogue action comprises a list of searchresults linked to a search engine based on the key word, and informationfrom the list of search results in a record related to the key word isincorporated in a record.
 39. A digital conversation generationapparatus, comprising: a memory; a processor disposed in communicationwith said memory, and configured to issue a plurality of processinginstructions stored in the memory, wherein the processor issuesinstructions to: create a dialogue agent; populate the created dialogueagent application on a dialogue platform; receive a dialogue action froman individual target via the dialogue platform; generate a dialogue linein response to the received dialogue action via the dialogue agent;record an interactive dialogue comprising the dialogue action and thegenerated dialogue line; retrieve the recorded interactive dialoguebetween the individual target and the dialogue agent; allocate a valuepoint to each dialogue element of the interactive dialogue; create adigital conversation asset comprising at least the retrieved interactivedialogue associated with the allocated value point to each dialogueelement of the interactive dialogue; determine a value for the digitalconversation asset at least based on the allocated value point to eachdialogue element of the interactive dialogue; and provide the createddigital conversation asset associated with the determined value forexchange.
 40. A digital conversation generating processor-readablenon-transitory storage medium storing processor-issuable instructionsto: create a dialogue agent; populate the created dialogue agentapplication on a dialogue platform; receive a dialogue action from anindividual target via the dialogue platform; generate a dialogue line inresponse to the received dialogue action via the dialogue agent; recordan interactive dialogue comprising the dialogue action and the generateddialogue line; retrieve the recorded interactive dialogue between theindividual target and the dialogue agent; allocate a value point to eachdialogue element of the interactive dialogue; create a digitalconversation asset comprising at least the retrieved interactivedialogue associated with the allocated value point to each dialogueelement of the interactive dialogue; determine a value for of thedigital conversation asset at least based on the allocated value pointto each dialogue element of the interactive dialogue; and provide thecreated digital conversation asset associated with the determined valuefor an exchange.